[8] Principles and Models of Solid Fuel Combustion

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THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

Principles and Models of Solid Fuel Combustion

Henrik Thunman

Department of Energy ConversionCHALMERS UNIVERSITY OF TECHNOLOGY

Göteborg, Sweden 2001

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HENRIK THUNMANISBN 91-7291-058-5

© HENRIK THUNMAN, 2001

Doktorsavhandlingar vid Chalmers tekniska högskolaNy serie nr 1742ISSN 0346-718X

Department of Energy ConversionCHALMERS UNIVERSITY OF TECHNOLOGYS-412 96 GöteborgSwedenTelephone +46 (0)31 772 1000

Cover: A burning piece (5cm long) of wood

Chalmers ReproserviceGöteborg, Sweden 2001

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Henrik ThunmanDepartment of Energy Conversion

Chalmers University of TechnologyS-412 96 Göteborg, Sweden

Abstract

Combustion of solid fuels stands for a substantial part of the heat and power production in theworld. In this thesis different aspects related to the thermochemical conversion of solid fuelsin fluidized and fixed beds are treated, such as: the combustion temperature of a fuel particlerelated to the surrounding temperature in a fluidized bed combustor (FBC); the fuel loading ina FBC; a transient description of the conversion of non-spherical fuel particles; thethermochemical properties and composition of volatiles released from wood; the thermalconductivity of wood during different stages of conversion; the modelling of a grate furnace;the general combustion behaviour of a fixed bed on a reciprocating or a travelling grate; andfinally, the design and construction of experimental units for investigation of combustion in afixed bed. The main result is a number of sub models validated by comparison withmeasurements. The sub models are to be used to describe and understand various combustionbehaviours. Besides the sub models derived, it is concluded that the generally acceptedbehaviour of combustion on a reciprocating or a travelling grate is not correct for wetbiofuels. Measurements and supplementary modelling show that the ignition of the bed is notcaused by reflection of radiation from specially designed arches in the furnace. Insteadignition takes place at the bottom of the bed, close to the surface of the grate. This isimportant for new designs of reciprocating and travelling grates.

Keywords: Biofuels, Coal, Combustion, Fixed bed, Fluidized bed, Fuel loading, Grate,Measurements, Modelling, Single particle, Thermal conductivity, Thermochemicalconversion, Thermochemical properties, Wood

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The thesis is based on the following Papers:

I. G.I., Palchonok, C., Breitholtz, H., Thunman, B., Leckner, ‘Impact of heat and masstransfer on combustion of a fuel particle in CFB boilers’, 14th International conceranceon FBC, Ed. F.D.S. Preto, ASME, 1997, pp. 871-878. (Awarded as best Paper)

II. H. Thunman, B. Leckner, ‘Fuel loading of a fluidized bed combustor’, 4th EuropeanConference on Industrial Furnaces and Boilers, Eds. W., Leuckel, J.,Ward, R.,Collin,A., Reis, INFUB, Esphinho-Porto, Portugal 1-4 April, 1997. (An appendix to thePaper is included from, H, Thunman, ‘Loading and size distribution of fuel in afluidized bed combustor’, Thesis for the degree of licentiate of engineering,Department of Energy Conversion, Chalmers University of Technology, Göteborg,May 1997).

III. Henrik Thunman, Bo Leckner, Fredrik Niklasson, Filip Johnsson, ‘Combustion ofwood particles – a model for Eulerian calculations’, Submitted for publicationJune 2001.

IV. H., Thunman, F., Niklasson, F., Johnsson, B., Leckner, ‘Composition of volatile gasesand thermo-chemical properties of wood for modeling of fixed or fluidized beds’,Accepted for publication in Energy & Fuels, August 2001.

V. H., Thunman, B., Leckner, ‘Thermal conductivity of wood during differentcombustion stages’, Submitted for publication February 2001.

VI. H., Thunman, L-E., Åmand, F., Ghirelli, B., Leckner, ‘Modelling and verifyingexperiments of the whole furnace’, Report to the European Commission JOR 3CT960059, Department of Energy Conversion, Chalmers University of Technology,Göteborg, Sweden, 1999.

VII. H., Thunman, B., Leckner, ‘Ignition and propagation of a reaction front in cross-current bed combustion of wet biofuels’, Fuel, 2001, 80, 473-481.

VIII. M., Rönnbäck, M., Axell, L., Gustavsson, H., Thunman, B., Leckner, ‘Combustionprocess in a biomass fuel bed – Experimental results’, Progress in ThermochemicalBiomass Conversion, Ed. Bridgwater, Tyrol, September, 2000.

Contribution by Henrik Thunman

Paper I. Henrik Thunman together with Timo Joutsenoja from Tampere University ofTechnology carried out the pyrometer measurements. Henrik Thunman carried out theanalysis of these measurements and the fundamental part of the modelling showing theignition phenomena. Claës Breitholtz and Gennadij Palchonok improved the modelconcerning heat and mass transfer to the single particle. Gennadij Palchonok summarised andwrote the article.

Paper II, V and VII. Henrik Thunman is the principal author.

Paper III and IV. Henrik Thunman carried out all work, except for the measurements and theevaluation of the measurements, which was carried out by Fredrik Niklasson.

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Paper VI. Henrik Thunman acted as a project leader, planed the survey measurements in thegrate furnace, evaluated the first measurement campaign, derived the bed model, supervisedthe CFD-calculation, and summarised the report. Lars-Erik Åmand had an active part in themeasurements, evaluated the second measurement campaign and made the conclusionsconcerning the NOx formation. Federico Ghirelli carried out the CFD-calculations as a part ofhis master degree thesis work.

Paper VIII. Henrik Thunman suggested the design of the two furnaces and the measurements.Monica Axell and Marie Rönnbäck constructed the furnaces and carried out themeasurements. Marie Rönnbäck wrote the paper.

Bo Leckner is the supervisor of this work and had an active role in the writing of all papers.Filip Johnsson is Fredrik Niklasson’s supervisor, and Lennart Gustavsson is Monica Axell’sand Marie Rönnbäck’s supervisor.

All the papers, I to VIII, were thoroughly discussed and edited by all co-authors.

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Contents

Abstract ..................................................................................................................................... iii

Acknowledgements................................................................................................................... ix

Introduction................................................................................................................................ 1

Furnaces and Reactors used for Experiments ............................................................................ 2

Summary of Papers .................................................................................................................... 5

Conclusions.............................................................................................................................. 19

Future Work ............................................................................................................................. 21

References................................................................................................................................ 21

Errata list for the included Papers ............................................................................................ 24

Populärvetenskaplig sammanfattning ( In Swedish )............................................................... 25

Paper I to VIII

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Acknowledgements

I would like to thank my supervisor Prof. Bo Leckner for his dedication in my work and forproviding me the opportunity to accomplish this thesis work. As well, I would like to thankhim for always being open for discussions and sharing his wide knowledge in the field ofenergy conversion.

I also would like to express my gratitude to all co-authors (Gennadij Palchonok, ClaësBreitholtz, Lars-Erik Åmand, Fredrik Niklasson, Filip Johnsson, Monica Axell, MarieRönnbäck, Lennart Gustavsson) and especially to Sven Andersson who introduced me intothe subject.

Finally, I would like to thank all colleagues that are or have been working at the departmentduring these years for providing a friendly and inspiring atmosphere.

This work was supported by a scholarship from the Nordic Energy Research Program forCombustion of Solid Fuels, and by grants from Swedish National Board for Industrial andTechnical Development (NUTEK), and Small scale Combustion Program of the NationalEnergy Administration. Part of the work was carried out under the European Union contractJOR3-CT96-0059. All of them are gratefully acknowledged.

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Introduction

The qualitative behaviour of the thermo-chemical conversion of solid fuels follows the samepath, independent of the combustion situation drying, devolatilisation, char combustion, orgasification. Depending on particle size and heating rate these processes can occursequentially or simultaneously in the solid fuel particle. Different aspects of the thermo-chemical conversion of solid fuels in fixed and fluidized beds are studied in this thesis, wherea number of sub models are derived for comprehensive models of conversion, and forevaluation and understanding of measurements. In the papers assembled, the following hasbeen investigated: excess temperatures of fuel related to the bed temperature (1123 K) in acirculating fluidized bed (CFB) combustor; fuel loading in a CFB combustor; the conversionrate of fuel particles in a fixed or fluidized bed; modelling of the combustion process in areciprocating or travelling grate furnace; and finally, general combustion behaviour of a fuelbed supported by a reciprocating or travelling grate.

The conditions (i.e. oxygen concentration, particle size) under which fuel particles canachieve a higher temperature than that of the surrounding in a CFB furnace, which can causeproduction of NOx or indicate bad mixing of the gas, are investigated in Paper I. For theinvestigation, measurements of surface temperatures on and heat and mass transfer to particlesinside the CFB combustor were carried out, supported by a model.

The importance of high excess temperatures can have on NOx production, for example, isstrongly connected to the size distribution and concentration of particles on different levels inthe furnace. These quantities determine the amount of particles that can achieve hightemperatures. The size distribution and the number of particles on different levels are a directmeasure of the fuel loading, which is the subject investigated in Paper II. The interest in thefuel loading is mainly for operation control; a small fuel loading gives a fast response to achange in the operating condition, whereas the opposite results for a large fuel loading. Workhas been carried out previously in this area [1 - 4], but mostly in small experimental units. Themeasurements in Chalmers 12 MWth CFB furnace provide data for comparison with theresults from these small units. For modelling of fuel loading a more extensive description isneeded of the conversion of the solid fuel particles than for the description of the surfacetemperature in Paper I. The model is therefore extended by the introduction of modelelements for drying, devolatilisation, fragmentation and attrition. However, significantsimplifications can be made due to the well defined surrounding of the single particles in afluidized bed. For example, the time t for drying and devolatilisation of spherical particle withthe diameter d can be described with a simple empirical correlation of the form t = a d b,where a and b are empirical coefficients, [4-6]. This description of drying and devolatilisationis appropriate for homogenous fuels with spherical form and can therefore be used for mostcoals.

For non-homogenous fuels or/and particles exposed to a transient environment, such as, in afixed bed or during changes in operation conditions in a fluidized bed, a transient particlemodel is needed. For example, biofuels entering the furnace have moisture contents that oftenvary with time and, therefore, require a particle model that describes the progress of thedrying and devolatilisation inside the particles. Furthermore, most biofuels have shapes thatare far from spherical. In Paper III, a transient model was derived for the combustion of singlefuel particles or groups of fuel particles in different beds. A great effort was made to minimisethe computational effort, without losing important features influencing the combustion, suchas shrinkage and particle shape.

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A transient combustion model requires a large number of fuel properties, among whichparticle size, shape and composition, thermal conductivity, specific heat and shrinkage duringconversion are the most important ones. In the assembled papers, for simplicity, fuelproperties are taken for trunk wood. However, the sub-models derived are general and can beused for various solid fuels. In Paper IV thermo-chemical data for wood during differentstages of combustion are summarised together with a model for the determination of thecomposition of the volatile gases leaving a fuel particle. These data are complemented inPaper V with a model for the thermal conductivity of wood during different stages ofconversion.

A fixed bed that is ignited from one end and with air introduced from the other, can be seen asa large fuel particle. The difference is that also air, introduced for the conversion of the fuelbed, follows the moisture and the volatiles through the bed and gives rise to internal heatgeneration by combustion. This combustion behaviour has been applied frequently because itis the generally accepted behaviour for combustion of a fuel bed on reciprocating or travellinggrates, [7-11]. In Paper VI a simplified bed model is derived, based upon this assumption andincluding the main features of conversion of the fuel bed along the grate. The purpose is toinvestigate the possibility to model the entire grate furnace by connecting a model of the fuelbed to models included in an existing CFD-software, for description of the gaseouscombustion above the fuel bed. For validation, extensive measurements in a 31 MWth

reciprocating grate furnace were carried out. As a consequence of the validation of the modelin Paper VI the assumed combustion behaviour of the bed model is questioned. This is furtherinvestigated in Paper VII.

To achieve a more detailed knowledge of the combustion behaviour in fixed beds, twoadditional small-scale combustors were built, Paper VIII. The validity of the measurementsfrom these units is assured by comparison with measurements from similar units found in theliterature. For supplementary analyses an additional model of the conversion in a fixed fuelbed is derived. This model is optimised for the determination of the maximum possiblepropagation rate of the reaction front in a fuel bed, ignited from one end and with airintroduced from the other end, Paper VII.

Furnaces and Reactors used for Experiments

In Paper I to VIII measurements were carried out in a number of test units: a 12 MWth

Circulating Fluidized Bed (CFB) combustor located at Chalmers University of Technology, a31 MWth reciprocating grate furnace located in Trollhättan (Sweden), three laboratoryfurnaces for investigation of the propagation rate of a reaction front in fixed beds, two at SP(Swedish National Testing and Research Centre, Borås Sweden), and one at VTT (TechnicalResearch Centre of Finland, VTT-Energy Jyveskylä, Finland). A laboratory scale fluidizedbed located at SP was used for investigations of single particles.

A general outline of the CFB combustor used in the experiments for Paper I and II is given inFigure 1. The primary air for combustion of the fuel and fluidization of the inert bed isintroduced in the bottom of the riser. The fuel is fed onto the inert bed and kept there until it isconverted. Circulating fluidized beds are operating at a gas velocity that is higher than the

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Fuelinlet

Furnace

heat-transfersurface

Flue gas

Air

Cyclone

Air

Wall

Primary Air

Fuel

Flue Gas

Ashes

Secondary AirSecondary Air

Flue GasCirculation

Flue Gas Circulation

Heat TransferSurfaces

Figure 1 General outline of the 12 MWth Figure 2 General outline of the 31 MWth

CFB combustor at Chalmers University reciprocating grate furnace in Trollhättan,of Technology. Cross-section of riser fabricated by Kvaerner Pulping AB.1.7×1.44 m, height 13.5 m. Grate cross-section 8×5 m, height 12.5 m.

terminal velocity of the inert particles, resulting in entrainment of inert and fuel particles bythe gas up through and out of the riser. The particles leaving the riser are separated from thegas in a cyclone and are reintroduced to the riser. The main advantage with fluidized bedcombustors is that primary measures can be taken for reduction of harmful emissions,facilitated by operation at a nearly constant temperature, and furthermore, that they are fuelflexible, as the fuel is kept in the inert bed until it is fully converted. The predominant primarymeasure is introduction of limestone for sulphur capture. The Chalmers CFB combustor isspecially designed for research and is prepared with a large number of measurement holes,allowing measurement probes of different kinds to be introduced into the combustor.Furthermore, the combustor is equipped with a large amount of measurement equipment and apermanent system for gas analysis. For the measurements referred to in Paper I and II, probeswere used for gas and particle sampling, heat transfer to a single particle, surface temperatureof burning fuel particles and for recording reducing and oxidising conditions.

An outline of the reciprocating grate furnace referred to in Paper VI and VIII is shown inFigure 2. This furnace is manufactured by Kvaerner Pulping AB and is operated byTrollhättan Energi AB as a part of the district heating system in the city of Trollhättan. In areciprocating grate the fuel is introduced from one end of the furnace and transported byreciprocating rods and burned along the grate. When the fuel reaches the other end of thegrate its conversion is finished and the remaining ash leaves the grate. The primary air forconversion is distributed in five zones along the grate to optimise the conversion of the fuel.For this project the furnace in Trollhättan was specially provided with measurement holes forprobes, and during the measurements the furnace was prepared with temporary equipment tomeasure the primary airflow and the temperature of the surface of the grate. Four types ofmeasurement probes where specially designed for the measurements, two for gas sampling,where one was combined with the measurement of gas temperature, one to measure the

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fluctuation between reducing and oxidising conditions, one for detection of the gas flowdirection.

The combustion of a fixed bed of biofuel was investigated in three units, Papers VII and VIII.Two of the units, one large and one small, where designed and built at SP, Figure 3 andFigure 4, and the third was designed and built at VTT, Figure 5, within the same project as themeasurements in Trollhättan. The work was focused on measurement of the propagation rateof the reaction front in a fixed fuel bed, and special experiments were carried out using thesame fuel as in Trollhättan. All these three units operate in the same way; a batch of fuel isplaced on a grate, air is introduced from one end, and the bed is ignited from the opposite endof the fuel bed. The propagation rate is evaluated from temperature measurements, which aremade in different positions, mainly along the height in the fuel bed. The large unit at SP andthe unit at VTT are prepared for gas analysis. There are differences between the units relatedto size and design, but the only major difference is in the design of the large unit at SP,Figure 3. This unit is up side down concerning the ignition and introduction of air comparedto the other two designs, Figure 4 and Figure 5.

For measurements on single particles, Paper III and IV, a small fluidized bed reactor,Figure 6, operating under bubbling conditions (gas velocity lower than the terminal velocityof the inert bed particles), was used. The reactor is electrically heated to the temperature ofthe experiments and particles were dropped into the reactor from the top. Gas leaving thereactor is sampled and analysed.

Scale

Air

DistributorPlates

Fuel

Flue gas

Holes forMeasurementProbes

Air

Flue Gas

Fuel

ThermoCouples

Figure 3 General outline of the large Figure 4 General outline of the smallexperimental furnace at SP. Combustion experimental furnace at SP. Combustionchamber cross-section 0.52×0.48 m, chamber diameter 0.2m, height 0.45 m.height 0.7 m

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Air

Flue Gas

Fuel

Thermo-couples

Scale

Gas sampling for analysis

I I

II II

III III

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Electricalheaters

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Gas samplingfor analysis

Flue gas

Quartz reactor

Figure 5 General outline of the experimental Figure 6 General outline of smallfurnace at VTT. Combustion chamber diameter fluidized bed reactor for single particle0.244 m, height 0.3 m. experiments at SP. Reactor diameter

0.056 m, height 1.4 m.

Summary of Papers

Paper ISurprisingly high temperatures of burning particles of bituminous coal, temperature levelsthat can be suspected to cause a production of thermal NOx in the surrounding gasfilms, weremeasured with a two-colour optical pyrometer in the upper part of the Chalmers CFBcombustor. Excess temperatures up to 600K above the bed temperature of 1123 K wereregistered, Figure 7a, while the cross-section average oxygen concentration was around 6%.The excess temperature in Figure 7a is plotted against the X-factor, which is an equivalentview factor of the particle in the view field of the pyrometer, obtained from the analysis of themeasurement. The X-factor for particles of different sizes located along the centre position ofthe view-field is shown in Figure 7b. In order to investigate at which oxygen concentrationsand particle sizes these high temperatures could exist, a diagram showing the ignitionbehaviour of a fuel was created, based on a simple heat balance of burning spherical particles,Figure 8. In the figure the Damköhler number, defined as the reaction rate divided by themass transfer coefficient, characterizes the ignition behaviour, as combustion goes fromkinetic control to diffusion control. By means of the diagram, it is possible to discuss thepossibility and conditions of high excess temperatures. The diagram can be built-up for alltypes of combustion conditions, but the paper focuses on the upper part of the CFBcombustor. From the diagram, Figure 8, it is seen that ignition takes place if the oxygenconcentration is above 8% and for fuel particle sizes of around 1 mm. This means that theoxygen concentration must be at least 1/3 higher than the cross-sectional average value beforeignition takes place. In order to get excess temperatures of more than 500K, the oxygenconcentration needs to be at lest twice as high as the highest measured average concentration,and the particle must be between 0.5 and 2 mm. The only explanation for the high particle

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a)

10 10 10 10 10-4 -3 -2 -1 00

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Figure 7 a) Temperature measured with two-colour pyrometry as a function of the X-factor.b) The X-factor as a function of distance from probe-tip, for different particle diameters.

temperatures measured must therefore be a wide fluctuation of local oxygen concentration,resulting from insufficient mixing. The presence of such fluctuations is confirmed bysimultaneous measurements of reducing and oxidising conditions. The time intervals duringoxidising conditions are short, and in order to allow a particle to have a sufficiently longresidence time in the oxygen-rich environment to be ignited, the particle must follow the gasup through the furnace. The ability of particles to follow the gas is given by the terminalvelocity, which in a gas flow is a function of the drag coefficient, and in a circulatingfluidized bed, enhanced by the collisions with surrounding small particles. In general, smallparticles are more likely to follow the gas than larger particles, and consequently it is morelikely that the smaller fuel particles experience long enough periods in oxygen-richenvironment to allow them to ignite and achieve high excess temperatures. Besides theanalysis summarised here, Paper I includes a large work on heat and mass transfer to a singleparticle, which is covered extensively in the doctoral theses [12] and [13].

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Figure 8 Excess temperature versus particle diameter for different oxygen concentrations(solid lines), and Damköhler numbers (dashed lines).

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Paper II

The fuel loading of a fluidized bed combustors affects the control of operation; a small fuelloading results in a fast response to changes in operating condition, whereas the opposite isachieved for large fuel loading. Here, a general model of fuel loading and size distribution offuel in a fluidized bed combustor has been developed. Specially, for the circulating fluidizedbed combustor is that the fuel concentration and size distribution are modelled along the riser.Devolatilisation is modelled with the classical empirical particle diameter power law (t=adb)and char combustion as a shrinking sphere exposed to a surface reaction. During bothdevolatilisation and char combustion the fuel undergoes fragmentation and attrition, which forthe fuel loading is nearly as important as the rate of devolatilisation and char combustion. Thefragmentation and attrition are to some extent treated in a new way. The new treatment is inthe definition of the rates of fragmentation and attrition, and size distribution of the fragments.A good agreement between model and measurements in Chalmers 12 MWth CFBC isobtained, Figure 9. The fragmentation rate constants obtained from the evaluation ofexperimental data also show a good agreement with rate constants from literature data. Themodel includes the most influencing parameters and is computationally efficient.

0.01 0.1 1 100

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Figure 9 Comparison between measured and modelled size distribution and fuelconcentration on different heights.

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Despite of the complexity of the fragmentation and attrition during combustion in a fluidizedbed combustor the model derived in this paper gives a good agreement with measurement byadjusting four empirical coefficients. The values of these empirical coefficients are severelyrestricted by both the resulting fuel loading and size distribution, and by the conversion of thesolid fuel. For example, in the measurements there are nearly no large particles found,indicating that the large fuel particles fragment almost immediately after they are introducedinto the combustor. This significantly reduces the fuel loading, which is a severe restriction onthe possibility to fit the fuel loading. Furthermore a large number of fuel particles found in thefly ash indicates the amount of particle produced by attrition, and limits the minimum rate ofattrition. The attrition also reduces the fuel loading, and to keep the fuel loading at themeasured level, which leaves the fragmentation rate during char combustion as the onlyparameter that are not directly restricted by the measurements. For the coal used in themeasurements it is concluded that this fragmentation rate must be rather small. Since, asignificantly larger fragmentation rate during char combustion would lead to a much lowerfuel loading than the measured one.

The parametric study shows that the fuel loading depends on type and size of fuel,fragmentation and gas pressure inside the combustor; all these parameters have a greatinfluence on combustion. A rise in pressure and/or superficial velocity increases the poweroutput from the combustor, and also the fuel loading. Bed temperature and air to fuel ratioalso have an influence on the fuel loading, but not as great as that of the other parametersinvestigated. The size distribution of fuel in the bed is mostly dependent on the fragmentationbehaviour of the fuel. For a CFBC, the superficial gas velocity mainly affects the variation offuel concentration along the riser.

Paper III

A simplified model of thermochemical particle conversion, independent of particle size andshape, is derived. The model operates with a small number of variables and treats the mostessential features of conversion of solid fuel particles, such as temperature gradients inside aparticle, release of volatiles, shrinkage and swelling, considering also typical shapes (spheres,finite cylinders and parallelepipeds). The model treats the particle in one dimension, and theconversion can be described by the heat and mass transport to the surface of the particle. Thederivation of a control surface of a finite cylinder is illustrated in Figure 10. When modellinga large combustion system, such as a fluidized bed or a fixed bed on a grate, this is a greatadvantage, as the model should not be limited to just a single particle. In fact, it can handle theconversion of a solid phase in a computational cell, where the conversion is related to surfacearea per unit volume instead of surface area of a single particle. The model divides the particleinto four layers: moist (virgin) wood, dry wood, char residue and ash. The development andthe temperature of these layers are computed as function of time, as shown in Figure 11.

The model is validated numerically by a heat and mass balance, and it agrees well withmeasurements performed on more than 60 samples of particles of different sizes, woodspecies and moisture contents. A comparison with experimental time of devolatilisation,Figure 12, and time of char combustion, Figure 13, shows that the substantial simplificationsmade do not severely influence the overall agreement of the model. The model calculationspredict the great influence from shrinkage on time of devolatilisation and char combustion.This is shown in Figure 14, which illustrates the influence of shrinkage for the largest particlesize of spruce used in the experiments 10×25×40 mm. In the figure the shrinkage by volumeduring drying and devolatilisation is chosen to 15, 35 and 45%. Larger shrinkage results in a

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more compact char layer, and consequently higher thermal conductivity and a shorter time ofdevolatilisation. On the other hand, for char combustion the trends are the opposite as shownby the model, because increased shrinkage means a smaller external surface. The shrinkagecoefficients used in the calculation are obtained from direct measurement, supported by aqualitative judgment of the fit between measured and calculated times of devolatilisation andchar combustion.

d/2d/2

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Figure 10 Definition of the starting position Figure 11 Example of simulatedof the radius r0 and the control surface Γ (solid temperature and positions of drying (1),line) at radius r inside a finite cylinder (dashed devolatilisation (2), char combustion (3)line) having a length l, longer or shorter than and particle surface (4) inside a wetthe diameter d. spruce particle as a function of time.

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Figure 12 Comparison between calculated Figure 13 Comparison betweenand measured time of devolatilisation for calculated and measured time of

61 samples of, wet (o) and dry ( ) spruce, char combustion for 61 samples of,

and wet (∗) and dry (+) birch. wet (o) and dry ( ) spruce, and wet (∗)

and dry (+) birch.

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Calculated time [s]M

easu

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Figure 14 Times of devolatilisation (o) and char combustion (∗). Arrows indicate theinfluence of increasing shrinkage.

Paper IVFor comprehensive models of combustion devices, for example fixed and fluidized beds, thereare a need of a sub model providing a sufficient composition of the volatile gases leaving afuel particle of typical sizes. The real composition of the volatile gases becomes too complexfor these models, since, for example, for wood the composition consists of more than 100species [14]. However, much work has been published on releases of volatiles [15-25], but ageneral model of the composition of volatile gases and a comprehensive presentation of therelated thermo-chemical properties of the fuel are still missing. Due to the complexity of thetransformation of the fuel, it becomes excessively time-consuming to model the gas leavingthe thermally large particles by means of a set of reaction rates. Because of time restrictions amore simplified description of volatile release is needed for comprehensive bed models. Here,a sub model is presented, whose structure is valid for any solid fuel. The model solves asystem of six equations to obtain the six gas concentrations. The system of equations consistsof three mass balances, one energy balance and two empirical ratios. In some cases,dependent on the available input data, the energy balance can be replaced by an additionalempirical ratio, and the energy balance can be used for validation. The model includesempirical coefficients, and they have to be specified for certain classes of fuel. Gases fromdevolatilization of the dry part of high-volatile fuel are assumed to consist of CO2, CO, H2O,H2, light hydrocarbons (mainly methane and ethylene), and lumped hydrocarbons (that is, theremaining hydrocarbons). The method proposed is for estimation of the quantities of these gascomponents in a case when no data are available, or for a measured set of data needed to bechecked.

In addition to the empirical ratios, thermo-chemical properties of the fuel during its variousphases of conversion are needed. Therefore, measurements have been carried out on two typesof wood to provide data that can be compared with data from literature. This collection of datais especially selected to suit combustion and high temperature gasification. The data arespecialized to wood. The measurements concern softwood (spruce) and hardwood (birch), butsimilar collection of data can be established for other fuels as well.

The measurements were carried out in a fluidized bed reactor operated at 1123 K and theresults show a clear correlation between the size of the fuel, expressed as specific area (initialsurface area divided by initial volume of the particle), and several quantities such as charyield, ratios of CO to CO2, and light hydrocarbon to CO2, Figure 15. As the specific areaincreases (size decreases) a nearly linear decrease of the char yield and linear rise of the ratios

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22

Specific Area [1/m]

Cha

r Yie

ld [%

]

300 600 9002.0

2.5

3.0

3.5

4.0

Specific Area [1/m]C

O/C

O2

(by

mas

s)

300 600 9000.8

1.0

1.2

1.4

1.6

1.8

Specific Area [1/m]

TH

C/C

O2

(by

mas

s)

300 600 9000.8

1.0

1.2

1.4

1.6

1.8

Specific Area [1/m]

H2O

/CO

2 (b

y m

ass)

0

10

20

γ H2O

x100

0

10

20

γ H2x1

000

0

10

20

γ CO

x50

0

10

20

γ CO

2x100

300 600 9000

10

20

γ CiH

jx100

Specific area [1/m]300 600 9000

10

20

γ CnH

mO

kx100

Specific area [1/m]

Figure 15 Ratios of THC to CO2, CO to CO2 Figure 16 Estimated composition ofand H2O to CO2, and char yield, related to the volatile gases, expressed as massspecific area of the wood particles, birch (wet, fractions, versus specific area, for+, dry, *, solid trend lines), spruce (wet, o, dry, birch (* solid line) and spruce (∇ and∇, dashed trend line). dashed line). (Observe the different

scaling factors).

of CO to CO2, and light hydrocarbon to CO2 can be seen. The lower char yield isaccompanied by an increasing amount of carbon relative to hydrogen and oxygen in thevolatile gases, which, together with the two ratios mentioned, affects the composition of thevolatile gases, since it favors the lumped hydrocarbons on the behalf of the carbon dioxide.The two tested woods, hardwood (birch) and softwood (spruce), show the same trends. Theonly differences are in the level of char yield and in amount of H2O in the volatile gases.Further work could involve other fuels and a more detailed investigation on the influence oftemperature. In the present work the most relevant temperature for the application wasstudied. Analysis of the measurement data with the model derived for the composition of thevolatiles, Figure 16, shows that the mass fractions of water, hydrogen, carbon monoxide andlight hydrocarbons are rather constant with specific area, but the level of carbon dioxidedecreases on the behalf of a rise of the mass fraction of lumped hydrocarbons.

Paper VThe effective thermal conductivity is one of the most important parameters for modelling ofthe thermo-chemical conversion of wood. It varies both with temperature and conversion ofthe wood. There are measurements available in the literature and suggestions on modelling ofthis problem, especially for wet and dry wood, but for char the knowledge is poor. Here, twoprincipal models of effective thermal conductivity on the basis of the pore structure in wood,[26] and [27], are validated by a comparison with direct numerical simulation of the fibrestructure. The validation leads to a more general model, both for conductivity in theperpendicular and parallel direction relative to the fibres in the wood. A secondary result isthat the thermal conductivity of the solid phase in the fibre wall of the wood can be evaluatedfor dry and wet fuel from measurement data on effective thermal conductivity. The effectivethermal conductivity can be estimated from given values of temperature, density and moisturecontent of the wood. It can also be applied to pellets and chipboards. In addition, the general

12

model expresses the effective thermal conductivity of char, since the wood material maintainsits fibre structure during conversion.

From the model, the thermal conductivity perpendicular to the fibre is estimated to0.52 W/mK for the solid material in the dry wood by a least-square fit to measurement datafrom [28] and other authors, reviewed in [29]. Parallel to the fibre, the corresponding thermalconductivity is estimated to 0.73 W/mK, based on measurements reviewed in [29]. Theagreement between the model derived here and the models of [26] and [27] and measurementdata can be seen in Figure 17, for dry wood, and Figure 18, for wet wood. There is goodagreement between all of the models and the measurement data for dry wood, but thedifference becomes noticeable if one regards the heat conductivity of the solid in the fibre. In[26] this heat conductivity is suggested to be 0.43W/mK, but in [27] it is suggested to0.6W/mK. If the values mentioned are inserted into their respective equations, there is an evenbetter agreement with measurements than the one shown in Figure 17, but for high densityfuels the difference becomes noticeable. If these values are used, for example, to estimate theheat conductivity of pellets, which have a high density (1000-1300 kg/m3), the differencebetween the models can be more than 15 %. When char is produced at a high heating rate andwith a high final temperature, the resulting porous structure is nearly pure carbon. Here, it isproposed that carbon in the porous structure has the same thermal conductivity and density asamorphous carbon.

0 500 1000 15000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Dry density [kg/m3]

Hea

t con

duct

ivity

[W/m

K]

0 0.1 0.2 0.3 0.4 0.50

0.1

0.2

0.3

0.4

0.5

Calculated thermal conductivity [W/mK]

Mea

sure

d th

erm

al c

ondu

ctiv

ity [W

/mK

]

Figure 17 Heat conductivity of dry wood as Figure 18 Comparison of measured,a function of density. Conductivity parallel [28], and calculated effective thermalto fibre (solid line with dots), measured data, conductivity perpendicular to the fibres[29] (stars). Conductivity perpendical to in wood, with a moisture contentibre, model derived here (solid line), model of 7-45% (based on wet wood).derived in [27] (dashed line), [26] (dotted line).Measured, [28] (circles), [29] (rhombs).

13

Paper VI

During the last decade the gaseous combustion in the free-room above the grate in areciprocating grate furnace has been modelled with different CFD (computational fluiddynamics) tools, where the combustible gas leaving the bed is distributed along the gratebased on the assumed combustion behaviour of the fuel bed. In the present work, anindependently derived bed model is connected to a CFD calculation of the gaseouscombustion above the bed, in order to model an entire furnace. The main task of the work isto investigate if the combustion of the fuel bed and the gaseous combustion above the bed canbe calculated separately, and then combined efficiently in an iterative calculation.

For this purpose a simplified bed model was derived, which separates the bed in four layers;surface layer, char layer, reaction front layer and virgin fuel layer, based on an assumedcombustion behaviour of the bed, Figure 19. For each layer a heat and mass balance isestablished, which describes the conversion of the fuel bed. The layers represent: the non-reacting layer of virgin fuel, the propagation of the drying, devolatilisation and gaseousreaction, the conversion of the char residue, the surface of the bed that is interacting with thesurrounding. Input to the model are data on the fuel fed, such as fuel properties, bed heightand porosity, and along the grate, such as equivalent radiation temperature for the radiationexchange with the surface of the bed, gas flow and velocity of the bed. The bed model givesresulting position of the reaction front, bed height, composition and temperature of the gas,and temperatures inside the bed, Figure 20.

Heat transfer and gas exchange between the bed and the free-room above the bed is used asboundary condition to the two models, which results in an iterative calculation procedure,where the equivalent radiation temperature above the grate is assumed first, and theconversion of the fuel bed is calculated. This is followed by a CFD-calculation of the gaseouscombustion above the bed, where surface temperature of the bed and temperature andcomposition of the gas leaving the fuel are used as boundary conditions. The heat flux to thebed resulting from the CFD calculation is recalculated to an equivalent radiation temperature,and used as a boundary condition for the fuel bed, and so on. The experience from thecalculations made is that the solution reaches convergence in just a few iterations.

Bed

hei

ght

Time or Length of grate

Reaction front

Char layer

Unreacted fuel layer

Surface layer

xs

xc

xr

xU

Primary air

Heat Flux

Figure 19 Schematic figure of the four layers describing the bed. The thicknesses of the layersare indicated by x and a subscript related to the layer.

14

0

400

800

1200

1600

2000

Tem

pera

ture

[K]

0

2

4

6

8

10

Out

goin

g M

olar

Flo

w [m

oles

/s]

0

0.1

0.2

0.3

0.4

0.5

Bed

hei

ght [

m]

0 1 2 3 4 5 6 7 80

2

4

6

8

10

Bed length [m]

Ingo

ing

Mol

ar F

low

[mol

es/s

] (In

put)

Char layerSurface layerSurrounding (Input)

CH4

COO

2CO

2H

2O

N2

0

0.2

0.4

0.6

0.8

1

Rel

ativ

e m

ass

loss

[−]

Bed surfaceReaction frontMass loss

0 1 2 3 4 5 6 7 80

1.5

3

4.5

6

7.5

Bed

vel

ocity

[mm

/s] (

Inpu

t)N2 (Input)

O2 (Input)

H2O (Input)

Bed vel. (Input)

Velocity change bedVelocity change gas

Figure 20 Input data and result of modelling. The grey areas indicate the given changes inthe primary airflow and velocity of the fuel layer along the grate.

15

In order to validate the models, extensive measurements on a commercial reciprocating gratefurnace were carried out for two different operating conditions. In these measurements gassampling and temperature measurements were made in more than 80 positions. Furthermore,continuous sampling was made of more than 30 operating parameters. Average data frommost of these measurements are reported in Paper VI, but some additional data can be foundin Paper VII. The extensive documentation of the measurement data in Paper VI and VIImakes the data useful for validation of new and existing models and for comparison withother furnaces.

The measurements in the lower part of the combustor show on a major combustion zone inthe first part along the grate, where the volatiles enter the furnace from the bed, and on a finalchar burnout in the later part along the grate. The measurements also show that the finalburnout of the gases leaving the bed takes place in a narrow region around the introduction ofthe secondary air. Furthermore, an internal circulation of gases in the upper part of the furnaceis seen from the measurements. When comparing the model calculations with themeasurements, there are clear indications on some general errors in the assumed combustionbehaviour made in the bed model, which is discussed in paper VII. However, in the upper partabove the secondary air inlet the gases from the lower part of the furnace are well mixed and abetter agreement between calculation and measurements is observed in this region.

Paper VIIGrate firing is the most common way to burn bio-fuels in small-scale units. Differentcombustion modes are achieved depending on how fuel and primary air are introduced. Incontinuous systems fuel and air are usually fed in cross-current and counter-current flow. InPaper VI the generally assumed combustion behaviour of wet biofuels was questioned and,therefore, the combustion in the mentioned 31 MW reciprocating grate furnace (a cross-current flow combustor) is further studied. For the investigation, additional experiments werecarried out in batch-fired pot furnaces, using the same fuel as in the reciprocating grate, forestwaste with a moisture content of approximately 50%. The generally accepted suggestion onthe combustion in a cross-current flow furnace is that it start by ignition on the surface of thebed, followed by a reaction front propagating from the surface down to the grate, [7-11].Measurements and visual observations presented here show, however, that in the case of wetfuels the ignition takes place close to the grate, followed by a reaction front propagating fromthe grate up to the surface of the bed. Hence, the progress of combustion in the bed is oppositeto the expected one. The measurement positions in the grate furnace are shown in Figure 21.

Figure 21 Position of measurements in the reciprocating grate furnace. Gas sampling ( ),Thermocouples ( ) (31 MW furnace, Kvaerner Pulping AB)

16

Figure 22 Principle combustion behaviours Figure 23 Measured time-averagein a cross-current flow unit. (a) if the bed temperature on the reciprocating grate.is ignited from the surface of the bed, or (b) Filled circles indicate measurementfrom the surface of the grate. A position with pure wood chips and unfilledindicates of ignition, B vertical view, C circles are measurement with forestreaction front, I unreacted fuel, II drying, waste.III devolatilisation, IV char combustion orgasification, V ash.

Figure 24 Total hydrocarbon concentration Figure 25 Calculated maximumabove the bed of the reciprocating grate. propagation rate of the reaction front forFilled circles indicate the second measurement 10mm wood particles, dotted lines. Solidrow and unfilled circles the first measurement lines are curve fits of the measurements.row (Cf. Fig 3). Measurements from operation The measurements are indicated bywith pure wood chips. capital letters and calculation with

small letters, the different moisturecontents are indicated by, A,a 10% [8],B,b 30% [8], C,c 40.3% (VTT) and D,d56.6% (SP).

17

The result from the investigation is that the progress of combustion can not be the onegenerally expected, shown in Figure 22a, according to following observation:

1. In the pot furnaces the reaction front could not propagate through the bed for the sametype of fuel and air flows as in the furnace, where the fuel burned without problems. Thisobservation is supported by the model calculations.

2. Even the highest velocity of the reaction front, 0.35 mm/s, measured for wood cubes witha moisture content of 10%, is not sufficient for the front to reach the surface of thereciprocating grate within the first 4 m, if the bed is ignited from the top. For a bed heightof 500 mm, it would take 1430 s for the reaction front to propagate from the surface of thebed to the grate. With the velocity of the grate, 6 mm/s, the reaction front would reach thegrate 8.6 m after ignition on the surface. The corresponding distance at velocitiesmeasured for wet fuels is 18 to 60 m. In contrast, in the furnace case, according to Figure23, the high temperatures clearly indicate that combustion takes place at or close to thesurface of the grate after less than 1.8 m.

3. The temperature on the grate, Figure 23, shows that heat was generated in the bed beforeignition was visually observed on the surface of the bed.

4. There was a heavy evolution of smoke from the bed before the position of ignition on thesurface of the bed and before the visible flame zone, according to visual observations inthe reciprocating grate furnace.

5. Volatiles were found far from the fuel inlet, Figure 24. A moist wood-chip particle (50%moisture) dries and devolatilises completely in two minutes at a temperature of 973K,[30]. The temperature inside the bed is around 1300K, [8] and Paper VIII, during charcombustion, and the actual time for complete drying and devolatilisation should be lessthan two minutes. The fuel is transported 0.7 m along the grate in two minutes. Ignition ismeasured within the first 1.8 m for pure wood chips on the reciprocating grate, Figure 23,and all moisture and volatiles should have left the bed before 2.5 m (1.8+0.7 m) distancefrom the feed point if the reaction had propagated from the top of the bed to the grate.However, Figure 24 shows that volatiles leave the bed up to 4-5 m from the beginning ofthe grate.

The conclusion from these facts is that the ignition has not taken place on the surface of thebed, but in the bed, most likely on the surface of the grate. The arguments supporting thisobservation and that reaction propagates up through the bed, Figure 22b, are:

1. In such a case, the theoretical maximum moisture content is attained when the lowerheating value for moist fuel is equal to zero. This occurs at a moisture content of 85 to90%, excluding heat losses. The reaction takes place inside the bed in a location that isquite well insulated from the surrounding. Moisture content of up to 70 or 80 % shouldtherefore generate sufficient heat for drying and devolatilisation. The heat is generated atthe bottom of the bed by char combustion and is transported up through the bed by thegas, which dries and devolatilises fresh fuel. For a counter-current bed, which is ignitedfrom the top, on the other hand, this moisture content is too high, since in this case,devolatilisation and combustion takes place in a narrow front. The calculation shows thatthe maximum moisture content the range of air flows considered is between 35 and 45%.It is also clear from the calculation that the velocity of the reaction front becomes veryslow for these moisture contents.

2. Combustion and heat release in the bottom part of the bed generates gas, which transfersits heat to the fresh fuel and exits the bed at a temperature, not much higher than that ofentering fuel particles. This explains the heavy evolution of smoke, observed to leave thefirst 1 to 1.5 m of the bed.

18

3. The reaction front propagates up through the bed and the devolatilisation continues untilthe devolatilisation front reaches the surface of the bed. This explains the volatile releasefar down on the grate, see Figure 22.

4. Ignition of the fuel on the surface of the grate takes place as soon as the fuel has reachedthe ignition temperature. Larger particles need longer time to heat up and ignite, andconsequently there is a later ignition of the pure wood chips than of the forest waste thatincludes a large portion of fine saw-dust, although the moisture content was 10% higher,Figure 23.

Large scale mixing of the fuel bed could be another reason for the temperature raise before1.8 m from the fuel inlet, but ignition or stirring caused by the transport of the bed along thegrate were not observed on the surface during the first 1 to 1.5 m from the fuel inlet. Anotherfact that talks against large scale mixing is the tendency of wood chips to stick together.

The low measured propagation rates of the reaction front in a wet fuel bed are confirmed to beclose to the theoretical maximum. This means that the propagation rate in a reciprocatinggrate cannot be that much higher in the same combustion situation, even if two-dimensionaleffects are present. The theoretical maximum is determined by a calculation where all ingoingparameters are chosen in favour of the propagation of the reaction front. In Figure 25 it is seenthat all measurement data, [8] and measurements carried out in the present work in the largeunit at SP and at VTT, are within or close to the theoretical maximum given by the model. Forthe highest moisture contents there can be observed a slightly higher propagation rate than thetheoretical maximum one. The reason for this is most likely that the moisture content of thefuel was somewhat lowered during ignition of the bed. A large part of the fuel had to be driedby the heat added for ignition before the fuel ignited, and during this time also the fuel belowdried by heat from the same heating source and from the convective air flow through the bed.

This result questions some design principles for grate furnaces: the ignition arches designed toreflect radiation from the flames to the bed surface to ignite the bed are not needed. However,the design of the furnaces may not change after all, since these arches also have positiveaffects on the gas flow in the furnace. When publishing this paper we did not find any supportfor this combustion behaviour in the literature. However, later on it was found that the sameobservation was made in [31], where combustion of wet cellulose on a laboratory travellinggrate was investigated. Furthermore, after submission of the paper measurements fromburning wood chips on a travelling grate was presented in [32], where the same combustionbehaviour is indicated in a small grate furnace. However, no conclusion was drawn exceptthat further investigation is needed.

Paper VIIIIn order to further investigate combustion of a fuel bed placed on a grate, two small batch-fired furnaces were designed and built. In the first furnace, the larger unit, air is introducedfrom the top end and ignition take place in the bottom end. This unit has the advantage thatheat transfer and thereby the ignition can be controlled. Furthermore, the relatively largesurface area of the grate gives a one-dimensional combustion behaviour and allows largerparticle sizes. The larger size also gives the opportunity to supply the unit with moremeasurement equipment and to penetrate the fuel bed with measurement probes without asignificant disturbance of the combustion behaviour, thus creating a better possibility tofollow the progress of the reaction front. The disadvantages consist in the difficulties ininterpreting the measurement results from inside the bed, as the relative position of thelocation of the measurement inside the bed changes as the bed shrinks away, as the reaction

19

0.0 0.1 0.2 0.3 0.4 0.5 0.6Air mass flow (kg/m²s)

0.00

0.02

0.04

0.06

0.08

0.10

0.12

Ign

itio

nra

te(k

g/m

²s)

Large test rig, pellet 8mmSmall test rig, pellet 8mm


0.00

0.02

0.04

0.06

0.08

0.10

0.12

Ign

itio

nra

te(k

g/m

²s)

wood 8 mmwood 10 mm, Gortwood 5-20 mm, Horttanainen

Figure 26 Measured ignition rate (coincide Figure 27 Ignition rate for 8-mm woodwith the propagation rate) in a bed of 8 mm cylinders, the small unit, 10-mm woodwood pellets as a function of airflow, in the cubes, [8], and 5-20-mm, [33], woodlarge and the small unit. chips as function of air mass flow rate.

front in the bed propagates from the grate to the surface of the bed. Furthermore, the grate, onwhich the fuel bed rests, must be provided with a few rather large holes, in order to avoid thegrate to clog. This results in an unwanted gas flow pattern close to the surface of the grate.

In the second furnace, the smaller unit, the air is instead introduced from the bottom and theignition takes place at the top. In this furnace the ignition and heat transfer to fuel bed surfaceis not controlled, but an even gas flow through the bed can easily be arranged and the relativebed position of the measurements inside the furnace is easier to approximate, as a positioninside the bed is fixed until the reaction front passes. The smaller unit is also much easier tooperate, which makes it more sufficient for initial and preliminarily experiments.

The performance of the two units was validated by comparing results from tests with fuelbeds of uniform fuel particles operated at different airflows with similar tests in other furnacesreported in the literature [8] and [33], Figure 26 and Figure 27. The comparison shows thatthe units built provide the expected behaviour and can be used for more detailedinvestigations in future work.

Conclusions

Paper I.Fluidized bed combustors are usually considered to be practically isothermal due to the goodmixing provided by the fluidization of inert material, which have a high thermal capacity.However, in the present work, measurements of surface temperature in a large scale fluidizedbed combustor show that the fuel particles can have excess temperatures of 500 to 600 K inrelation to the bed temperature. Model calculations show that these excess temperatures onlycan be present at higher oxygen concentrations than the mean concentration measured in thecombustor. This indicates that the mixing is not as good and the temperature is not as even asexpected.

20

Paper II.A general model of fuel loading and size distribution in a fluidized bed combustor (FBC) hasbeen developed. For the circulating fluidized bed combustor (CFBC) the fuel concentrationand size distribution along the riser are also modelled. The fragmentation is to some extenttreated in a new way. The fragmentation rate constants obtained from the evaluation ofexperimental data show a good agreement with the literature data. The model accounts for themost influencing parameters and is computationally efficient.

Paper III.Modelling of a great number of large solid fuel particles in a combustion system needs amodel that account for the most essential features of the conversion process with as fewequations and as small computational effort as possible. The model presented here treatsparticles that change in size during conversion and are realistically shaped. The modeldescribes the conversion of the fuel particles in a one-dimension formulation, which makes itsuitable for Eulerian calculations. A comparison of the model with experiments shows that thesimplifications made do not significantly influence the overall agreement of the model.

Paper IV.When modelling combustion systems, especially of high volatile fuels, a representation isneeded of the composition of the volatile gases. In the present work, a sub model for thecomposition of the volatile gases leaving particles that are non isothermal during conversionand fulfils the elemental species and energy balances of the fuel is derived. The model isvalidated for wood and the physical properties required for the modelling are summarised.

Paper V.When modelling combustion of large wood particles, the thermal conductivity is one of themost important properties, since internal heat transfer in most cases is decisive for theconversion rate of the solid fuels. Previously there have been suggestions on how to model thethermal conductivity of wet and dry wood, but the models differ slightly. Therefore a moredetailed investigation, based on modelling, has been carried out. The result of theinvestigation is a more general model and suggestions on how to model the thermalconductivity of char.

Paper VI.A simplified bed model is derived for the combustion behaviour of a cross-current(reciprocating) grate furnace. The model accounts for the most essential physical processes ofthe conversion of the fuel bed along the grate that are modelled and based on the generallyaccepted combustion concept. The concept presumes that a reaction front propagates from thesurface of the bed down to the surface of the grate. The bed model is successfully connectedto a CFD-calculation of the gaseous combustion above the grate by an iterative procedure. Formodel validation, a survey is made of the different gas concentrations in the furnace bymeasurements in a 31 MW grate furnace. Comparison with measurements from a 31 MWth

reciprocating grate furnace shows a good agreement in the upper part of the furnace, but thelower part indicates that there are some fundamental controversies in the model assumptionsfor the bed (To be treated in Paper VII).

Paper VII.The generally expected combustion behaviour of cross-current furnace is that the bed isignited on the top of the bed by radiation from the flames and ignition aches (assumptionmade in Paper VI). However, the present paper shows that this is not the case, especially for

21

wet biofuels. The measurements performed both in the large scale furnace and in laboratoryfurnaces show that the ignition has to start close to the grate, which means that it starts on theopposite side related to what is generally expected. This conclusion explains why the bedmodel derived in Paper VI did not properly work for the investigated grate furnace.

Paper VIII.In order to further investigate the propagation rate of a reaction front moving in the samedirection as the one generally expected in cross-current combustion, two furnaces wereconstructed and their functionality is proven by comparing measurement data with similarunits found in the literature.

Future Work

In the papers assembled in the present thesis a number of models are derived. They can becombined in different ways and be complemented for further use and analysis ofmeasurements performed. There are also test facilities built up for future investigation,especially for the combustion in a fixed bed. The work that will hopefully be done in the nearfuture is to introduce the transient model for single particles into a general bed model, forsupplementary evaluation of measurement data obtained from the small grate furnaces builtand the reciprocating grate. Further, there are still a large part of the measurements carried outduring this work that are not analysed; both from the reciprocating grate furnace and the CFBcombustor. For example, a third measurement campaign was carried out in the reciprocatinggrate in Trollhättan. Other interesting work for the future is to formulate a transient model forthe fuel loading in the CFB combustor, and to extract more information on the oxygenfluctuations in the CFB combustor, based on the surface temperature measurements.

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25. Di Blasi, C., Branca, C., Santoro, A., Gonzalez Hernadez, E., ‘Pyrolytic behaviour andProducts of Some Wood Varieties’, Combustion and Flame, 2001, 124, 165-177.

26. Siau, J. F., ‘Transport Processes in Wood’, Springler-Verlag, Berlin, ISBN 3-540-12574-4, 1984.

27. Saastamoinen, J. J., Richard, J-R., ‘Simultaneous Drying and Pyrolysis of Solid FuelParticles’, Combustion and Flame, 1996, 106, 288-300.

28. MacLean, J. D., ‘Thermal Conductivity of Wood’, Transactions American Society ofHeating and Ventilating Engineers, 1941, 47, 323-354.

29. Grønli, M, ‘A Theoretical and Experimental Study of the Thermal Degradation ofBiomass’, Academic Dissertation, The Norwegian University of Science and Technology,ISBN 82-471-0009-6, 1996.

30. Palchonok, G.I., Dikalenko, V.I., Stanchits, L.K. Borodulya, V.A., Werther, J. andLeckner, B. ‘Kinetics of the Main Stages of Fluidized Bed Combustion of a wet biomassparticle’, Proc. of the 14th Int. on Fluidized Bed Combustion, Vancouver, Canada, F.D.S Pretoed, ASME, New York, 1997, 125-134.

31. Lamb, B.W., Bilger, R.W., ‘The combustion of wet cellulosic fuel bed’, SecondAustralasian Conference on Heat and Mass Transfer, The University of Sidney, 1977, 501-508.

32. Weissinger, A., Fleck, T., Obernberger, I, ’Investigation on the Release of Nitrogen andVolatile Compounds from the Fuel Bed in Grate Furnaces’, 1st World Conference onBiomass, Seville, Spain, 2000.

33. Horttanainen, M.V.A., Saastamoinen, J.J., Sarkomaa, P.J., Ignition front propargation inpacked beds of wood particles, IFRF Combustion Journal, www.ifrf.net, Article Number200003, ISSN 1562-479X, May 2000.

24

Errata list for the included Papers

Paper IPage 871 col. 2 line 5: “U-V/ε” should be “U/ε-V”

Page 871, a notation is missing: max – largest diameter of a inert or active particle

Page 873 Eq (1); “2

1 /a im m+” should be “

2

1 /i am m+”

Page 873 col. 1 line 33: “and the inert (bed) particle of density ρb,c. The expression2/(1+ma/mi)” should be “ and the suspension of density ρb,c. The expression 2/(1+mi/ma)”

Page 873 col. 2 line 21: “ times an amount of heat absorbed” should be “times an amount ofheat absorbed per unit temperature difference”

Page 875 in Figure 2b: “di, mm” should be “da, mm”

Page 875 caption to Figure 3 line 7: “the solid line … of 9.4 mm …” should be “The dashedline … of 9.4 mm …”

Page 877, an acknowledgment is missing: The authors would like to thank Timo Joutsenoja,Plasma technology laboratory, Tampere University of Technology, Finland, for help withpyrometer measurements.

Paper IIPage 5 Eq (26): part (1) “ D ext g fuel fuelC A v vρ ” should be “ / 8D ext g fuel fuelC A v vρ ”, in part (3)

“ ( )inertR R+ ” should be “ ( )2

inertR Rπ + ”

Page 12 2nd reference “Siciliano, L.,” should be “Salatino, P.,”

Page 12 a reference is missing: Stubington, J.F., Moss, B., ‘On the Timing of PrimaryFragmentation During Bituminous Coal Particle Devolatilisation in a Fluidized BedCombustor’ The Canadian journal of chemical engineering, 1995, 73, 505-509.

Appendix Page XII Eq (A48): “ ( )0,... ...volF y+ + ” should be “ ( ),... ...f volF y+ + ”

Appendix Page XVII reference missed for Brown et al. [1992]: should be“Brown R.C., Ahrens, J., Christofides, N., ‘The Contribution of Attrition and Fragmentationto Char Elutriation from Fluidized Beds’, Combustion and Flame, 1992, 89,95-102”

Appendix Page XIX definition missed for Ff2,char: should be

“ ( ) ( ) ( ) ( )max

* * * *2, ,,

R

f char n char char f char

R

F R h R R M h R k R dR= ∫ ”

25

Populärvetenskaplig sammanfattning ( In Swedish )

Bakgrund

Under alla tider har olika typer av fasta bränslen såsom ved, torv och kol använts föruppvärmning och under de senaste seklerna för värme och kraftproduktion. För det senare ärkol den idag, och i alla fall under detta sekel, det enskilt viktigaste bränslet. Förbränningen avkol skapar dock både regionala och globala problem. Regionala problem är främst utsläpp avsvaveloxider, kväveoxider samt tungmetaller. Globala problem är främst utsläpp avväxthusgasen koldioxid. Under de senaste årtiondena har intresset för att skapa ett uthålligtenergisystem och att reducera produktionen av växthusgaser ökat. Ett steg i denna riktning äratt ersätta kol med förnyelsebara alternativ. För fasta bränslen består dessa i huvudsak avrester från skogs- och jordbruksindustrin. Målet med detta arbete och med all forskning inomdetta område är att öka förståelsen för förbränningen i syfte att minimera påverkan på miljönoch samtidigt producera el och värme till en så låg kostnad som möjligt.

Generella förlopp

Oberoende om fasta bränslen förbränns i en liten eldstad eller i en stor panna för värme-och kraftproduktion är förbränningsförloppet detsamma. Bränslet torkar, avgasar och slutligenförbränns, eller förgasas, den återstående koksen. Under torkningen avgår fukten från bränsletvid en lokal temperatur omkring 100 °C. Den efterföljande avgasningen är när bränslet brytsner pga. uppvärmning och avger sina flyktiga beståndsdelarna, vilket sker itemperaturintervallet 300 till 600 °C. Avgasningen kan illustreras av de gaser som gerflammorna runt brinnande grillkol. Den slutliga koksförbränningen eller förgasningen är närkoksen reagerar med luftens syre eller med t.ex. vattenånga och koldioxid. Detta kanåskådliggöras med glödande grillkol. Dessa förlopp sker antingen var för sig eller samtidigtinne i bränslet beroende på storlek och med vilken hastighet bränslet värms upp.

Avhandlingens innehåll

Denna doktorsavhandling består av åtta arbeten där olika aspekter av omvandlingen ellerfysikaliska storheter för att beskriva omvandlingen av fasta bränslen i en rost eller enfluidiserad bäddpanna undersöks. Det som utreds i avhandlingen är följande:

• Bränslepartiklar med en mycket högre temperatur än omgivningen i en fluidiseradbädd

• Bränslemängden i en fluidiserad bädd.• Transient beskrivning av omvandlingen av icke-sfäriska bränslebitar med hög fukt-

och flykthalt.• Termokemiska data och sammansättningen av gaser som lämnar ett träbränsle under

avgasning.• Värmeledning i trä under olika stadier av förbränningen.• Modellering av en hel rostpanna.• Fastställande av det generella förbränningsförloppet i en bränsle bädd på en rörlig

rost.• Konstruktion och byggande av experimentanläggningar för undersökning av

förbränningsförloppen i en fast bädd.

26

Resultat

De huvudsakliga resultaten av arbetet är olika modeller, vilka är validerade motgenomförda mätningar. Härledningen av modellerna baseras på olika fysikaliska modeller ochkan inkluderas i övergripande modeller av förbränningen av fasta bränslen i fasta ellerfluidiserade bäddar, samt för att öka förståelsen av förbränning av fasta bränslen. Utöver deframtagna modellerna är det fastlagt att den allmänna uppfattningen om förbränningsförloppeti en rörlig rostpanna eldad med våta biobränslen inte stämmer. Istället för att förbränningen avbädden tänds med hjälp av strålning från flammor ovanför bädden, visar mätningar och enmatematisk analys, att bädden istället tänds underifrån, nära den rörliga rosten. Detta kan fåen stor betydelse för konstruktionen av nya rostpannor, då detta arbete visar att dereflekterande ytorna ovanför bädden som är avsedda för att underlätta tändningen inte hardenna funktion.

Paper I

14th International Conference on Fluidized Bed Combustion, Vancouver, May 11-14, 1997

871

!"#$

1A.V.Luikov Heat and Mass Transfer Institute, Academy of Sciences of BelarusP.Brovka 15, 220072 Minsk, Belarus

Phone:+375 17 268 4059, Fax:+375 17 232 1325

2Chalmers University of Technology, Department of Energy ConversionS-412 96 Göteborg, Sweden

Phone:+46 31 772 1431, Fax:+46 31 772 3592

High excess temperatures of burning coal particles, up to600 K, have been measured with a two- color pyrometer in thetransport zone of a CFB boiler at a rather low average oxygenconcentration of about 6 %. To understand this phenomenon, amodel of heat and mass transfer between a burning charparticle and its surrounding has been developed, based onmeasured heat transfer coefficients and the estimated slipvelocity of a char particle. The gas-convective and radiativemechanisms of heat transfer were found to dominate in thecore of the transport zone of a CFB furnace. The gas-convective transfer rate was 1.5 times as high as in a single-phase flow. Model calculations show that particles between 0.3and 3mm could have as high a temperature as the measuredones, provided that there is a highly non-uniform oxygendistribution over the furnace cross-section.

a,b,c,d stoichiometric coefficients in reaction (12), -cp specific heat, J/(kg*K)D molecular gas diffusivity, m2/sDa Damköhler number, kc/β, -d particle diameter, mE activation energy, J/molF function of particle size ratio in Eq. (7)g gravity acceleration, m/s2

kapp apparent combustion rate, m/skc chemical reaction rate, m/sko frequency factor, m/sm particle mass, kg, and factor in Eqs (3), (4)N number of collisions, 1/(m2 s)Nu active particle Nusselt number, α da/λ, -p split factor in Eqs (13), -Q heating value, J/Kq heat transferred during one particle collision, JR universal gas constant, 8.314 J/mole KRet particle Reynolds number, Ut,a d/ν, -r reaction rate kg O2/m

2 sS larger-to-finer particle size ratio, -Sc Schmidt number, ν/D, -

Sh Sherwood number, β da/D, -T temperature, Kt time, sU superficial gas velocity, m/sUt particle terminal or slip velocity, U-V/ε, m/sV particle velocity, m/sx distance between particle and probe tip, mYO2

oxygen mass fraction, -

%#&'α heat transfer coefficient, W/(m2 K)β mass transfer coefficient, m/sδeff effective thickness of a gas lens, mε voidage, -εr emissivity, -φ split factor in Eqs (13), -κ projected area of inert particles in a unit volume, 1/mλ gas thermal conductivity, W/(mK)ν gas kinematic viscosity, m2/sρ density, kg/m3

σ Stefan-Boltzmann constant, 5.67·10-8 W/(m2 K4)Θ angle of impact, rad

"&'( 'a active particleb bedc core regione endg gasgc gas-convectivei inert particleminsmallest diameter of inert or active particleo initialpc particle-convectiver radiatives solidt terminal or slip velocity

872

Fluidized bed combustors of stationary (SFB) orcirculating (CFB) type are usually regarded as isothermalsystems. The bed temperature is kept at about 1123 K tooptimize sulfur removal, to prevent oxidation of air nitrogenand ash melting. However, the particle phase is a mixture of afew active fuel particles, around 1 % by mass, and numerousinert ones: sand, ash and limestone. This makes the fluidizedbed locally non-isothermal. During the drying and, to someextent, during devolatilization, the fuel is colder than the inertmatrix of particles, but during char combustion the fuel iswarmer than the surrounding bed.

Numerous measurements, e.g. Borodulya et al. (1988),have shown that the excess temperature of large char particlesburning in an SFB at an oxygen concentration of 21%, reachesup to 500 K and decreases nearly linearly with oxygenconcentration. High local temperatures have to be consideredwhen analyzing formation of pollutants, combustion efficiencyand agglomeration in a fluidized bed combustor. Thetemperature of a burning particle is the result of therelationship between the chemical reaction rate and the heatand mass transfer rates to or from the particle. The heat andmass transfer coefficients of an active particle in a SFBcombustor can be reasonably accurately calculated with modelsavailable in the literature, e.g. Leckner (1992). The samemodels can also be applied to the dense bottom bed of a CFBcombustor, but there are no reliable data on the heat and masstransfer to an active particle in the upper zone of a CFBcombustor. A Froessling type of equation, e.g. used by Basuand Nag (1993), has not been experimentally proven underCFB conditions. Such a calculation is based on the slipvelocity of an active particle which can be affected by themotion of the inert particles. Besides, the turbulence of theexternal gas flow can significantly enhance the heat and masstransfer rate. Estimates of turbulence in the transport zone of aCFB combustor, caused by bubble eruption in the bottom bed(Palchonok et al., 1996), have shown that the turbulenceintensity in the gas phase is around 20 %. According toKutateladze (1990), this leads to an increase in the gas-convective heat and mass transfer rate with approximately 50%. An analogy can be made with the gas-convective heattransfer in the freeboard of a bubbling bed, which has beenfound to be 50 to 70 % as high as in a non-disturbed singlephase flow (Hassan and Palchonok, 1992).

There is also a lack of experimental data on thetemperature of the burning particles in a CFB combustor. Thedata available are limited to a few measurements with largefixed fuel particles in small-scale reactors. The excesstemperatures of the fuel particles have been found to vary from150 to 200 K (Bis et al., 1994), to 300 K (Krobarth et al.,1993).

The transport zone of CFB combustors is characterized bya non-uniform lateral distribution of solids concentration andbed temperature (Leckner and Andersson, 1992). Close to thewalls, a layer of descending particles is formed, in whichstrong gradients of the above parameters are observed, whereasthe distribution is rather uniform in the core of the bed. Thefalling velocity of 0.17 and 0.26 mm bed particles (silica sand)was found to be, respectively, 1.3 m/s (Wu et al., 1991) and

2.2 m/s (Golriz and Leckner, 1992). These values are close tothe terminal velocity of a bed particle, which implies that thegas velocity is small within the wall layer and that thecombustion occurs mostly in the core of the bed. The gasvelocity in the core is therefore higher than the superficialvelocity and can be assumed to be uniform there.

The present paper aims at improving the knowledge of theheat and mass transfer and temperature of burning charparticles in the core of a CFB, based on measurements in quitea large scale CFB combustor.

)

Measurements were carried out in the 12 MWth CFB boilerat Chalmers University of Technology described, e.g. byPalchonok et al. (1995). The combustion chamber has a 1.72 mby 1.44 m cross-section and is 13.5 m tall. Two of the fourwater-cooled membrane walls are refractory-lined. The testholes used in the measurements are situated in the center of thecool walls at heights 3.8, 8 and 11 m above the air distributor.The bottom bed temperature, 1123 K, was kept constant.

Heat transfer coefficients to fixed metal spheres of 5, 10and 15 mm in diameter were measured with the transienttechnique described by Palchonok et al. (1995). Theinstantaneous overall heat transfer coefficient was evaluatedfrom the natural heating rate of the sphere measured by anembedded thermocouple. A method of dark (oxidized steelsphere, εr=0.8) and light (ground silver sphere, εr =0.35)calorimeters was used to evaluate the radiative component ofthe heat transfer coefficient. The time-average local bedtemperature was measured with a K-type thermocoupleprotected with a double radiation shield. The probes werepositioned outside the boundary layer whose thickness wasaround 0.1 m on all the three measurement levels. Two silicasand fractions with Sauter mean diameters of 0.35 and 0.22mm, and density 2600 kg/m3, were used as bottom bedmaterials. The superficial gas velocity varied from 1.8 to 4.6m/s during the measurements with the larger inert particles andfrom 1.5 to 2.7 m/s with the smaller ones. The cross-sectionalaverage bed density at the measurement level varied from 1 to35 kg/m3.

The temperature of burning particles of bituminous coalwas measured with a two-color optical pyrometer developed byHernberg et al. (1993). The temperatures of the bed and of theactive particle were calculated from the measured ratio of theincident radiation intensities at two wavelengths. Themeasurement volume was a diverging cone with an aperture ofaround 12 degrees. The model assumptions used in thepyrometry were: (i) the inert solids are gray bodies of the sameemissivity; (ii) only one active particle is contained at themoment in the measurement volume; (iii) the wavelengths usedare selected to avoid an influence of the flue gas. The opticalpyrometer was contained in a water-cooled probe of 43 mmdiameter positioned at a height of 3.8 m with the tip placedclose to the axis of the furnace. The superficial gas velocitywas 4 m/s in the bottom bed and 6 m/s at the measurementlevel, because of the added secondary air. The bed materialwas silica sand of 2600 kg/m3 density and with a Sauter meanparticle diameter of 0.27 mm in the bottom bed and 0.25 mm atthe measurement level. The cross-sectional average bed density

873

was 25 kg/m3 and the oxygen concentration was 5.7 % at themeasurement level. The fuel was a bituminous coal.Simultaneous measurements of the instantaneous oxygenconcentration with a zirconia cell showed fluctuations betweenoxidizing and reducing conditions.

$#'' '*

The transfer rate is closely related to the flow patternaround the burning particle. An active char particle generallyhas different size and density from that of inert bed material.This results in a velocity difference between the active and theinert particles. A simplified situation, where spherical activeparticles with the parameters da, ρa and Va are surrounded byinert particles with the uniform parameters di, ρi and Vi , isconsidered for application in the model of Nowak et al. (1996).This model describes a quasi-steady state motion of a coarseactive particle (da>>di, Va<Vi) during the upward flow of adilute, uniform suspension of gas and inert particles. Becauseof the higher velocity, the inert particles collide with the sternof the active one. The collisions are assumed to be elastic, i.e.the restitution coefficient is equal to 1. As a result of theadditional momentum transfer, the velocity of the activeparticle increases compared to the case of a single-size particleflow. In the present analysis, analogous to that of Nowak et al.(1996), an arbitrary active-to-inert particle size ratio isassumed, which results in a modified equation for the slipvelocity,

( ) ( )

024

241

2

,,2

,

,,,,,

2

=−+

+−−+

+

D

DWDW

J

D

J'

LWDWLWDW

FE

LD

LD

ρπ

ρπ

(1)

The first - collision - term of Eq.(1) can be interpreted as adrag force, acting on the active particle having an effectivecollision diameter (da+di), caused by the difference in velocitybetween the active particle (fuel) and the inert (bed) particle ofdensity ρb,c. The expression 2/(1+ma/mi) is an effective dragcoefficient of the solid phase. The second term describes thedrag of the gas, where the drag coefficient is calculated as(Kovensky, 1996)

( ) 75.4,, 44.0Re24

FDWJ' ε+= (2)

The local bed density in the core, ρb,c, is approximately twotimes as low as the cross-sectional average bed density, ρb

(Zhang et al., 1994). The latter was evaluated from pressuredrop measurements.

It follows from Eq.(1) that the inert particles can eitherpromote the movement of a slow (coarse) char particle orhinder a fast (fine, low-density) one. Equation (1) wasobtained under a number of simplifying assumptions, and theprediction from this equation should be considered as a roughestimate.

The overall heat transfer coefficient is assumed to be thesum of gas-convective, particle-convective and radiativecomponents, α = αgc + αpc + αr. The gas- convective

component is calculated with a Froessling-type equation basedon the slip velocity,

33.05.0, PrRe2DWJF

+= (3)

The parameter m was evaluated from the measurements withthe fixed metal spheres. Equation (3) can be used forcalculation of the mass transfer coefficient, provided that theanalogy holds between the gas-convective heat transfer andmass transfer,

33.05.0,Re2 DWJF

+= (4)

The Sherwood and Schmidt numbers in Eq. (4) are based onthe molecular gas diffusivity of oxygen in the flue-gas. Thisdiffusivity was approximated with the one for a binary mixtureof oxygen and nitrogen, and calculated according toPomerantsev et al. (1986),

( ) ( )( )( )( )

5.0

21

215.26 273273273104.18

++++

⋅= −

(5)

where C1=138 and C2=107. This correlation is in agreementwith the Chapman-Enskog theory (Bird et al., 1960).

The particle-convective component is estimated, consistentwith the flow pattern described above, as a number ofcollisions per unit time per unit surface of the active particle,N, times an amount of heat absorbed by a single inert particleduring a short impact, q. According to Nowak et al. (1996)

( ) ( )( ) ( )322,, 123

LDLDLWDWGGGG881 πε +−−= (6)

The model of Zabrodsky (1966) for an elementary act of heattransfer between a surface and a single particle is used tocalculate q; a derivation is given in Appendix A. The modelassumes that the heat is transiently transferred through the gaslens between the relatively flat surface of the larger particleand the smaller spherical particle. A quasi-steady temperatureprofile in the film is assumed. The minimum effectivethickness of the lens was estimated as d/6. An analogousestimate for two contacting spheres of an arbitrary size ratio, S= dmax/dmin, reads

( )( ) πδ 2/13112161 2min +−−+=

HII(7)

( )( )6) 1arcsincos1−=

Provided a short duration of impact, which can be estimated ast=di/(Ut,a-Ut,i), the final expression for the particle-convectiveheat transfer coefficient reads

( )( )( )( ) 22183DLDFHIISF

+−= εδλα (8)

If the temperature of the inert particles does not changesignificantly during the short impact time, the radiative heattransfer coefficient is calculated as

( )( ) ( )111 ,,22 −+++=

EUDUEDEDU εεσα (9)

Emissivities εr,a=0.85 of char (Ross et al., 1981), and εr,i=0.6 ofinert (sand) particles (Borodulya et al., 1982) were used in the

874

calculations. The effective emissivity of the dilute isothermalsuspension was calculated as (Borodulya and Kovensky, 1983)

31.0,, LUEU

εε = (10)

#( "* &"+( '

A simplified heat balance of a burning spherical charparticle yields

( ) ( )EDJ2DSSDDDDS −−= αρρ2

6, (11)

The particle Biot number is assumed to be low enough toneglect the internal temperature gradient. A first-orderchemical reaction is assumed to occur on the external surfaceof the particle,

22 &2G&2F2E&D +=+ (12)

The molar ratios of the reactants and the primary reactionproducts are assumed to depend on the particle size andtemperature according to Arthur (1951) and Field et al. (1967)

[ ]D

7GFS /6240exp2500 −=≡ (13)

( ) ( ) S

31005.0;222 −⋅≤++=≡φ

( ) ( )

( ) PGS

GS

S

S

S

333

3

1011005.0;2

1095.0

1005.022

−−−

−

⋅<<⋅+

⋅

⋅−−+

=φ

S

3101;1 −⋅≥=φ

The above kinetics are questionable under SFB conditions(Prins, 1987) and (Hayhurst, 1996), but can be accepted for thedilute conditions in the CFB transport zone. The heat releaseof the chemical reaction per kg O2 is, derivation in AppendixB,

( ) ( )122

−+−= φφ&2&2

(14)

22 84.6;34.122

&2&2 ==

The apparent combustion rate constant (related to theconsumption of oxygen) is

( )β111 += FDSS (15)

The chemical reaction rate constant (related to oxygenconsumption) is assumed to follow the kinetics of Field et al.(1967),

( )( ) [ ]DDF

757N 149200exp22412321 −= φ (16)

Equation (16) implies the same reactivity for different coals,which differs from recommendations of Pomerantsev et al.(1986). An alternative kinetics of Pomerantsev et al. (1986)was also used, and this predicts a somewhat lower reaction rateat high temperatures,

[ ]N N ( 57F D

= −0 exp (17)

[ ]log . 042 0 2 10= + ⋅ −

the apparent activation energy, E, being 115 to 135 kJ/mole forbituminous coals.

The gas-convective heat transfer coefficients, evaluatedfrom the measurements as αgc = α - (αpc + αr), are presented innon-dimensional form in Fig. 1. The particle-convectiveconstituent was found to be negligibly small, 0.5 to 1.7 % ofthe total heat transfer coefficient, at the actual bed densities inthe core region, 0.5 to 17.5 kg/m3. The radiative constituentwas 20 to 30 % for the silver probes and 40 to 60 % for thesteel ones. A least square fit yields a value of the factor m inEqs. (3) and (4) of 1.02, with Ret based on the superficialvelocity. Provided that no gas flows through the 0.1 m thickwall layer, (Zhang et al., 1995), the gas velocity is around1.3*U/ε, which leads to the following expressions

JF W D= +2 0 89 0 5 0 33. Re Pr,. . (18)

JF W D= +2 0 89 0 5 0 33. Re ,. . (19)

Equations (18) and (19) predict approximately 1.5 times highertransfer rate than the Froessling equation (m=0.6) for singlephase flow. This agrees with the above mentionedrecommendation of Kutateladze (1990) and implies that theturbulence intensity is higher than 10 %, in the same order ofmagnitude as estimates of Palchonok et al. (1996). The

Fe Ag

200 1000

10

20

40

60

400 2000Reynolds number, Re

Gas

con

v. N

usse

lt nu

mbe

r, N

u

gc

t,a

600

15105

Figure 1: Nusselt number for gas convection betweena sphere and the bulk bed in the transport-zone. TheReynolds number of the particle is based on the localgas velocity. The symbols are for measured values,with 5, 10 and 15 mm spheres of steel, (filled), andsilver (open) (Palchonok et al., 1995). The largesymbols are measured with di=0.35 mm and thesmall ones with di=0.20 mm. The line is calculatedfrom Eq. (18).

875

reference temperature in Eqs. (18) and (19) is defined asT=0.5(Ta+Tb). The standard deviation from Eq. (18) in Fig. 1is around 30 %.

The results of the particle temperature measurements arepresented in Fig. 2a. The majority of the measured particleexcess temperatures were below 200K, but excess temperaturesup to 600K were recorded. The dependence of the measuredexcess temperature on the active particle diameter can beevaluated with a statistical routine. This statistical routinedemands a higher measurement accuracy than that obtainedand therefore, the excess temperature versus an X-factordependence is plotted directly in Fig. 2a. The X-factor is anexpression of the configuration factor for radiative exchangebetween the active particle and the probe, the extiction of the

radiation from the fuel particle due to inert particles, and theemissivites of the active particle and the bed. Assuming theemissivities to be close to unity, the X-factor can berepresented simply as a function of the configuration factor andthe extinction. The configuration factor was estimated as theratio of the projected area of the active particle and the area ofthe field of view. The extinction depends on the distancebetween the particle and the probe tip, x, and on the projectedarea of inert particles in a unit volume, κ, and so thetransmission becomes exp[-κx]. The field of view increasesproportionally to the distance from the probe tip, whereas thetransmission decreases exponentially. Estimates of the X-factorversus the distance form the probe tip for different activeparticle diameters are plotted in Fig.2b. It is seen from Fig. 2athat excess temperatures up to around 600 K have beenobserved, the highest values corresponding to low X-factors. Alow X-factor corresponds to either a small particle close to theprobe tip or a larger particle further away, but when no hightemperatures are observed at higher X-values the conclusion isthat only small particles have high excess temperatures.

The particle temperature is measuerd at a fixed location inthe furnace (an Eularian approach), but for the calculation ofthe particle temperature from Eq(11) the particle is assumed tofollow its environment (a Lagrangian approch). This problemcan hardly be solved, because of the variety of the motionpatterns of the particles and of combustion conditions. Forinstance, in a situation with strongly non-uniform oxygendistribution, Lyngfelt et al. (1996), a fine particle, easilycarried away with the gas, can follow either oxygen-rich or

10 10 10 10 10-4 -3 -2 -1 00

200

400

600

800

Exc

ess

tem

pera

ture

, K

X-factor, -

10 101010

10-3

10

10

10

-1

0

-2

-4

-3 -2 -1

0.2

0.5

1

2

5

Distance from the probe tip, m

X-f

acto

r, -

i

0.1

d , mm

Figure 2: a) Temperature measured with two-colorpyrometry as a function of the X-factor. b) The X-factor as a function of the distance from the probe-tip,for different particle diameters.

0

500

1000

1500

0 100 200 300 400

Time, s

Part

icle

tem

pera

ture

, KFigure 3: Experimentally determined temperaturehistories of burning char particles from bituminouscoal in an oxygen concentration of 21 %. The solidline is for a char particle with an initial diameter of 13mm in a bed with a temperature of 805 to 825 Kconsisting of fire-clay particles with a diameter of 2.15mm and a density of 2300 kg/m3. The solid line is fora char particle with an initial diameter of 9.4 mm in abed of fire-clay particles having a diameter of 0.83mm and a temperature of 990 to 1015 K.

876

oxygen-poor gas streams, while a coarse particle most likelywill face a fluctuating oxygen concentration. Therefore themeasurements have been compared with the quasi-stationaryform of Eq. (11), when dTa/dt = 0. The complete solution ofEq. (11) should look like Fig. 3, showing some coarse charparticle temperature histories measured at 21 % O2 in alaboratory-scale stationary fluidized bed. The experimentalcurves have two plateaus, the first one corresponding to aquasi- steady state, a kinetically controlled combustion regime.A small permanent increase of the bed temperature, which wasobserved during the measurements, interrupted the thermalequilibrium and the second plateau was reached,corresponding to a quasi-steady state, a diffusion-controlledregime.

Some stationary solutions of Eq. (11) for a 0.5 mm charparticle are shown graphically in Fig. 4, where the heat release,QkappYO2

ρg, (solid lines)and heat loss from the particle, α·(Ta-Tb) (dashed line), are plotted versus the excess temperature.The kinetics of Field et al. (1967) were used. Depending on theoxygen concentration, one or three steady state solutions canbe found, the intermediate one in the last case being unstable,as can be shown in terms of the Semenov (1935) ignitiontheory.

No char particle larger than around 4 mm has been foundat the measurement level, and this size was chosen as themaximum diameter of the char particles in the calculations. Allthe solutions in the field of interest are presented in Fig. 5,which shows the excess temperature versus particle diameterfor different oxygen concentrations and Damköhler numbers,Da. The Damköhler number is defined as the ratio of thereaction rate coefficient, kc, and the mass transfer coeffcient, β.If Da < 1, the combustion is controlled by kinetics, and ifDa>1 it is diffusion-controlled. A comparison between Fig. 5and Fig. 2a shows that the high measured excess-temperatures

could not be reached at the measured average oxygenconcentration YO2

=5.7%. Provided that the measurements andthe evaluation are correct, the highest temperatures can beattributed to fine char particles, e.g. products of secondaryfragmentation, following oxygen-rich gas streams. Assuminglocal plug-flow conditions, the maximum excess temperatureof 500 to 600 K is reached by particles of 0.3 to 3 mm indiameter. This agrees with the conclusion drawn from thecomparison of Figs. 2a and 2b. Somewhat lower excesstemperatures, but still consistent with the experiment, wereobtained with the kinetics of Pomerantsev et al. (1986). Otherreasons for the detected high temperatures, such ashomogeneous volatile combustion, can not be excluded. Thebulk of the excess temperatures lower than 200 K in Fig. 2acan be attributed to relatively large char particles, which didnot follow the gas and which therefore, on the average, meetrather low effective oxygen concentrations.

A model of heat and mass transfer to and from a burningchar particle in a CFB furnace is presented, based on thedifference between the velocities of fuel particles, bed particlesand gas. The gas-convective and radiative mechanisms of heattransfer are the dominant ones under the conditions prevailingin the core region of the transport zone. The gas-convectivetransfer rate is 50 % as high as in a single-phase flow, implyinga significant turbulence intensity in the gas phase.

Extremely high maximum excess temperatures of theburning particles, up to 600 K, were measured at a rather lowaverage oxygen concentration. This agrees with theoreticalpredictions, provided that oxygen is non-uniformly distributedover the furnace cross-section, and that fine char particlesfollow the gas flow and may burn in regions of high oxygenconcentrations.

0 200 400 600 800

Excess temperature, K

0

12·105

10·105

8·105

6·105

4·105

2·105

Hea

t rel

ease

/tran

spor

t, W

/m²

0.11

0.07

0.03

Y =0.15O2

Figure 4: Heat supply by combustion (solid lines) fordifferent oxygen concentrationsYO2

and heat removalby heat transfer (dashed line) for a 0.5 mm charparticle as a function of the excess temperature.

2

1

0.5

0.1

0.2

Particle diameter, m

Exc

ess

tem

pera

ture

, K

600

500

400

300

200

100

010 10 10

-2-4 -3

Da=5 10

1412

109

8

764

16

Y ,% O2

Figure 5: Excess temperature versus particlediameter for different oxygen concentrations (solidlines), and Damköhler numbers (dashed lines).

877

,-

The work was financed by the Swedish National Board forIndustrial and Technical Development (NUTEK) and by theINTAS grant No. 94-4313.

Arthur, J.R., Reactions between Carbon and Oxygen,Trans.Faraday Soc., 47, 164, (1951).

Basu, P., Yan, J., Characterization of the Fine CharParticle Combustion in Circulating Fluidized Beds, 12th Int.Conf. on FBC, Eds Rubow L. and Commonwealth G., ASME,(1993), 283.

Bird, R.B., Steward, W.E., Lightfoot, E.N., TransportPhenomena, John Wiley and Sons, New York, (1960).

Bis, Z., Gajevski, W., Nowak, W.,CFB Combustion andHydrodynamic Modelling, Proc. 2nd Int. Interfluid Symp. onFluidized Bed Combustion, Nagoya, (1994), 141.

Borodulya, V.A., Ganzha, V.L., Kovensky, V.I.,Hydrodynamics and Heat Transfer in a Pressurized FluidizedBed, Minsk, Nauka I Tehnica, (1982) (in Russian).

Borodulya, V.A., Kovensky, V.I., Radiative Heat Transferbetween a Fluidized Bed and a Surface, Int.J.Heat MassTransfer, 26, 277, (1983).

Borodulya, V.A., Palchonok, G.I., Vasiljev G.G., Dryabin,V.A. Galerstein, D.M., Heat and Mass Transfer andCombustion Kinetics of Solid Fuel in Fluidized Bed,Int.School-Seminar Heat and Mass Transfer Problems inAdvanced Solid Fuel Combustion and GasificationTechnologies, Minsk, (1988), 2, 3 (in Russian).

Field, A.M., Gill, D.V., Morgan,B.B., Hawksley, P.G.W.,Combustion of Pulverized Coal, BCURA, Leatherhead,(1967).

Golriz, M.R., Leckner, B., Experimental Studies of HeatTransfer in a Circulatig Fluidized Bed Boiler, 1st Int. Conf.Engineering Application of Mechanics, Tehran, (1992).

Hassan, A.F., Palchonok, G.I., Heat Transfer in theFreeboard of Fluidized Bed, Izvestija Vuzov: Energetika,No.4, 73-81, (1991) (in Russian).

Hayhurst, A.N., Advances in Coal Combustion, JointMeeting of the Portuguese, British, Spanish and SwedishSections of the Combustion Institute, The Combustion InstituteMadeira, (1996), P. 13.1.

Hernberg, R., Stenberg, J. and Zethræus, B, SimultaneousIn Situ Measurements of Temperature and Particle Size ofBurning Char Particles in a Fluidized Bed Furnace by Meansof Fibreoptic Pyrometry, Combustion and Flame, 95, 191-205(1993)

Kovensky, V.I., Account for the Constraining of ParticleMotion in the Freeboard, Presented at the Int. Workshop onthe INTAS project No.94-4313, Chalmers University ofTechnology Gothenburg, (1996).

Krobarth, P., Winter, F., Hofbauer, H., Reactivity of LargeCoal Particles under Fast Fluidized Bed Conditions, NordicSeminar on Solid Fuel Reactivity, Gothenburg, (1993), P. 6.

Kutateladze, S.S., Heat Transfer and HydrodynamicResistance: a Reference Book, Energoatomizdat, Moscow,(1990).

Leckner, B., Andersson, B.-Å., Characteristic Features ofHeat Transfer in Circulating Fluidized Bed Boilers, PowderTechnology, 70, 303, (1992).

Leckner, B., Palchonok, G.I., Andersson, B.-Å.,Representation of Heat and Mass Transfer of Active Particles,Presented at IEA Mathematical Modelling Meeting,International Energy Agency, Turku, (1992).

Lyngfelt, A., Åmand, L.-E., Leckner, B., Progress ofCombustion in the Furnace of a Circulating Fluidized BedBoiler, 26th Symp.(Int.) on Combustion, Combustion Institute,Naples, (1996).

Nowak, W., Bis, Z., Gajewski, W., Matsuda, H., Hasatani,M., Carryover of Coarse Particles from a Dense Bed in aMulty-Solid Fluidized Bed, Preprints of the 5th Int.Conf. onCFB, Beijing, (1996), P. DGS11.

Palchonok, G.I., Breitholtz, C., Andersson, B.-A., Leckner,B., Heat Transfer in the Boundary Layer of a CirculatingFluidized Bed Boiler, Preprints of the 7th Int.Conf. onFluidization, Engineering Foundation, Tours, (1995), 177.

Palchonok, G.I., Johnsson, F., Leckner, B.,Estimates ofTurbulence Effects in CFB Boilers, Preprints of the 5thInt.Conf. on CFB, Beijing, (1996), P. MSD7.

Pomerantsev, V.V., Arefjev, K.M., Ahmedov, D.B.,Fundamentals of Practical Combustion Theory, edV.V.Pomerantsev, Energoatomizdat, Leningrad, (1986).

Prins, W., Fluidized Bed Combustion of a Single CarbonParticle, Ph.D.Thesis, Twente University, Netherlands, (1987).

Ross, I.B., Patel, M.S., Davidson, J.F., The Temperature ofBurning Carbon Particle in Fluidized Beds, Trans.IChemE, 59,83, (1981).

Semenov, N.N., Chemical Kinetics and Chain Reactions,Oxford University Press, London, (1935).

Wu, R.L., Lim, C.J., Grace, J.R., Brereton, C.M.H.,Instantaneous Local Heat Transfer and Hydrodynamics in aCirculating Fluidized Bed, Int. J. Heat Mass Transfer, 34,2119, (1991).

Zabrodsky, S.S., Hydrodynamics and Heat Transfer inFluidized Beds, M.I.T. Press, Cambridge, Mass., (1966).

Zhang, W., Johnsson, F., Leckner, B., Characteristics ofthe Lateral Particle Distribution in Circulating Fluidized BedBoilers, 4th Int. Conf. on CFB Technology, Ed A.A.Avidan,AIChE, Hidden Valley, (1994), 266.

) ..

The particle convective heat transfer coefficient iscalculated as the product of the heat transfered during onecollision, q, and the number of collisions, N, divided by thetemperature difference between the active particle and thebulk.

( )EDSF −=α (20)

( )( )0,,3

, 6 LHLLLLS −= πρ (21)

Ti,0 = Tb is the temperature of the inert particles before impactand Ti,e is the end temperature after the impact and Ti,e-Ti,0=∆T.Zabrodsky assumed a quasi-steady temperature profile in the

878

effective gas lens, which is considered as a flat disc of δeff

thickness, δeff; this leads to:

( ) ( )( )( ) LDLHIILLLLS −= 46 23, πδλπρ (22)

Integrating from t=0 to the end of impact gives

( ) ( )[ ]LDHLL

−−−=− exp10,,0, (23)

where

( )LLSLHII ,23 ρδλ= . (24)

For a short impact time (k·t<0.03) the exponential expression,[1-exp(-k·t)]≈k·t, which leads to

( )( )( ) EDHIIL −= δλπ 42 (25)

The impact duration can be estimated as t=dmin/(Vi-Va). dmin isthe smallest of the diameters of the inert and active particle.The number of impacts

( )( ) ( )2

2

3

4

6

1

D

LD

LL

DLFL

G

GG

G

991

ππ

πρερ +−−

= (26)

Finally,

( )( )( )( )( ) 22min183

DLDLFHIISF +−= εδλα (27)

The minimum effective thickness of the lens formed duringa perfect contact between an inert particle and an infinitelylarge particle (a flat surface), related to the projected area ofthe inert particle, is δeff,min =(dmin/6). The real curvature of thelarger particle adds something to the minimum thicknessdmin/6. Moreover, the particles are in relative motion during theimpact, which should further increase the time averagethickness of the lens. Actually, the present estimate of thecollision time t is a twice the time for the smaller particle topass a distance dmin/2 to and from the surface. For a direct (θ =0) elastic collision, such an estimate implies the time averagelens thickness to be

4minSHUIHFWHII

+= δδ (28)

For an arbitrary angle, δeff=δperfect+dmincos(θ)/4. Averaging overθ = 0 to π/2 leads to

πδδ 2minSHUIHFWHII

+= (29)

When carbon is oxidized, carbon-dioxide is formed withthe reaction rate r1,

22 &22& →+ , (30)

but also carbon-monoxide with the reaction rate r2,

&22& 22 2 →+ . (31)

The split factor, φ, between coal and oxygen consumption isthen,

( ) ( )2121 2 UUUU ++=φ (32)

which leads to the following set of equations.

( ) ( ) 021 21 =−+− φφ UU (33)

VF&NUU =+ 21

where Cs is the concentration at the surface and the reactionrate coefficient, kc, is related to the consumption of oxygen.The solution for the reaction rates is:

( )VF

&NU φ−= 21 (34)

( )VF

&NU 12 −= φ

In the last equation, dimensions are optional: either (mole O2)or (kgO2/m

2s). Finally, the heat production becomes

( ) ( )12 minmax −+−= φφ 444 . (35)

Paper II

FUEL LOADING OF A FLUIDIZED BED COMBUSTOR

Henrik Thunman and Bo LecknerDepartment of Energy ConversionChalmers University of Technology

Abstract

This is a study of the influence of operatingconditions on the loading and size distribution offuel in a fluidized bed combustor and on thevertical fuel concentration in a circulating fluidizedbed combustor (CFBC). For this purpose a modelhas been developed including the most importantparameters and having a short calculation time, 30sec on a Sun Ultra.

The fuel loading depends on type of fuel,fragmentation and pressure; all these parametershave a great influence on the combustion. A riseof pressure and/or superficial velocity increases thepower output from the combustor, and also the fuelloading. The size distribution of fuel in the bedis mostly dependent on the fragmentation behaviorof the fuel. For CFBC, the variation of fuelconcentration along the riser is mainly affected bythe superficial velocity.

KeywordsFluidized bed, fuel loading, fragmentation, fuel sizedistribution, parametric study

1 Introduction

The heat release of a flame combustor respondsinstantaneously upon a change in the fuel feed rate. Abed combustor fired with solid fuels, and especiallya fluidized bed combustor (FBC), shows a certaintime-delay between a change in the fuel feed rateand the corresponding change in the heat releaserate. Similar time-delays occur for other changes inconditions, such as in air supply or bed temperature.The reason is, of course, that the fuel loading ofthe bed reacts with a certain delay depending on itssize and time of combustion. The time-delay maycause additional difficulties for a control system,since the fuel loading of a bed is not necessarilyconstant, it depends on a number of factors in acertain boiler: type of fuel, bed temperature, airsupply (secondary/primary) etc., and it depends ontype of boiler: fluidization velocity and pressure. Thefuel load has additional effects: the fuel distributionin the furnace and the surface temperatures of thefuel particles are important parameters needed for

an understanding of formation and destruction ofemissions, especially NO and N2O.

The purpose of this work is to investigate howdifferent operation conditions influence fuel loadingand size distribution of fuel. The model developedfor this purpose shall have a short calculation timeand shall include the most important influencingparameters.

2 Theory

Most models for fuel loading in FBCs aredeveloped for coal combustion, where the time ofdevolatilization is short compared with the timeof char combustion, and the devolatilization canbe assumed to be immediate e.g. Arena et al.[1995]. This assumption is not suitable for a generalmodel, because the devolatilization time for manyfuels, especially biofuels, is a large part of the totalcombustion time. A special case of the FBC is thecirculating fluidized bed combustor (CFBC), wherematerial is transported up through the furnace and acertain amount of the fuel is above the inlet of thesecondary air. This has not a great effect on the fuelloading, since most fuel is still in the bottom part ofthe furnace, but it can be of interest for formationand destruction of pollutants.

2.1 General models for the FBC

The assumptions made in the present model are:

• The bed is fed with a fuel having a knownRosin-Ramler size distribution.

• Devolatilization and fragmentation start im-mediately when the particles enter thecombustor.

• The devolatilization follows a shrinking coremodel and the fragmentation is proportionalto the mass of the fuel particles.

• The char combustion follows a shrinkingsphere model.

• During char combustion, the mass loss dueto fragmentation and attrition are treated likea surface reaction rate constant.

• The loss of efficiency from the combustor isdue to small char particles carried away bythe flue gases. The particles have a known

Feed Fuel

Fragmentation

Feed Char

Fragmenta-tion

Fly-ash

VolatilesChar

Devilati-lization

CharCombustion

Fuel transformation

Part

icle

siz

e

Figure 1. Principle scheme of the transformation of fuel in a fluidized bed combustor. The bars represent themass of char or volatiles entering a particle size fraction, the boxes represent models fordevolatilization and char combustion and the arrows represent mass flow from feedfuel entering the system to char leaving the system with the flue gases, Fash

size distribution taken from Chirone et al.[1991]

The fuel load of the bed is calculated from a massbalance over the combustion of the fuel. A principlecalculation scheme for the mass balance is shownin Fig. 1.

2.1.1 Devolatilization

The time of devolatilization, td, is represented by theempirical relationship, e.g. Zhang [1987], Stubingtonand Moss [1995], Winter [1995],

(1)

where R is the particle’s radius and a and b areconstants related to the fuel. By introducing theassumption of a shrinking core, the part of thevolatiles remaining in the fuel particle becomes,

(2)

x is the ratio of mass of volatiles at time andinitial mass of volatiles. is the time passed fromthe beginning of devolatilization. Under steady stateconditions if there were no fragmentation the massflow of the devolatilizing fuel particles at time is,

(3)

F is the mass flow of fuel at a time and Fchar,0 isthe initial mass flow of the char in the fuel havingthe particle size R. Vdev is the fraction of volatilesin the fuel. Assuming fragmentation of fuel particlesto be proportional to the mass, which, under steadystate condition, is proportional to the mass flow, themass flow of the fuel particles at time becomes fora certain size element around R,

F (R; ) =Fchar;0(R)(1 Vdev(1 x(; R)))

exp(kf;dev(x0))(1 Vdev)exp(kf;dev)(4)

kf,dev is the fragmentation rate constant and x0 isinitial relative volatile content. The probability,Pf,dev, that a particle of certain size R fragmentsduring devolatilization is,

(5)

This expression for the probability has the sameform and gives nearly the same result as morecomplicated models, e.g. Chirone et al. [1991],where the fragmentation is related to models of theinternal stress.

During devolatilization the particles fragment intosmaller particle sizes with a certain size distribution,

and volatiles and char are considered separately (Fig.1). The contribution of fragments to a certain particlesize element centred at R of the initial mass flow,F0(R), makes the average volatile content of the totalmass flow of fuel, x0, particle size element less thanthe volatile content of the initial fuel,

(6)

Ff1,dev is the mass flow of the volatiles in thefragments and Ff1,char is the mass flow of the charin the fragments. The initial mass flow of char witha certain size is,

(7)

By integrating Eq. 4 over all radii and overdevolatilization time, the total mass of solid fuelduring devolatilization, Mdev is obtained,

(8)

with the boundary conditions,

(9)

Rmax is the largest particle size in the size distributionof the particles fed. The size distribution, hdev,related to the total mass of solid fuel accumulatedduring devolatilization is

(10)

The fuel leaving the devolatilization stage for charcombustion is,

(11)

2.1.2 Char Combustion

The model expressing the total mass during charcombustion and the size distribution related to themass of char particles during char combustion is inprinciple the same as the one presented by Salatinoet al. [1989], which is an extension of the massbalance presented by Kunii and Levenspiel [1969].The difference between the model presented hereand the one of Salatino et al. is that secondary

fragmentation and attrition are not treated separately.Instead, here the different size distributions of thefragments from attrition and secondary fragmentationare represented by a single size distribution. Therate of fragmentation is treated as a surface reactionrate constant, similar to the attrition models in theliterature, e.g. Arena [1991], Chirone [1991]. Themass balance during char combustion is,

(12)

with the boundary condition,

(13)

Fash is char leaving with the flue gases, Mchar totalmass of char during char combustion, hchar sizedistribution of the char, Ff2,char mass flow of thefragments from larger particle sizes, and kf,char isfragmentation rate constant. The terms in Eq. 12correspond to

1. Feed char from devolatilization2. Char leaving with the flue gases3. Char entering or exiting the interval due to

char combustion4. Mass reduction in the size interval due to

combustion5. Mass entering the interval from previous

fragmentation6. Mass leaving the interval due to fragmenta-

tion

The char combustion is assumed to follow ashrinking sphere model. The shrinking rate is,

(14)

Mc is molecular mass of carbon, CO2 average oxygenconcentration in the bulk, c density of the carbon inthe char, kc surface reaction rate constant, splitfactor for CO and CO2 and is mass transfercoefficient. The split factor is calculated accordingto Arthur [1951] and the mass transfer coefficientfrom Sherwood number,

(15)

DO2 is molecular diffusivity of O2. Sherwood’snumber is calculated according Halder et al. [1985]

(16)

b is bed voidage, Re Reynolds number based onslip velocity and Sc is Schmidt number.

The particle temperature is obtained from the heatbalance,

(17)

Hc is heating value for carbon oxidation, tot totalheat transfer coefficient, T particle temperature, Tb

bulk bed temperature, r radiative, and c convectiveheat transfer coefficient.

2.1.3 Distribution of fragments

The fragments are assumed to be spherical, theirnumber is distributed according to a first ordergamma distribution and their masses according to afourth order gamma distribution. The fragments mustbe smaller than the mother particle, a requirementthat makes it necessary to normalize the distribution.The size distribution on a number basis, hf,n and ona mass basis, hf, is

(18)

y is the radius of the fragments and is a scale factorcontrolling the shape of the distribution. The meansize of the fragments is assumed to have the samerelative radius, , for all initial particle sizes,

(19)

y*mean is the mean size of the fourth order gamma

distribution (not normalized). If the relative radiusis large (>40) the normalized distributions can besimplified,

(20)

During devolatilization the particles fall apart into afew large particles, Chirone et al. [1991] and Chernand Hayhurst [1996]. The relative radius is thereforebe large during devolatilization, and the distributionfollows Eq. (20). During char combustion, thefragments come from the fines produced by attritionand secondary fragmentation, Chirone et al. [1991].If attrition is dominant, the relative radius issmall ( <0.05), and if secondary fragmentation isdominant, the relative radius is large ( >0.5). Theerror caused by the size distribution chosen, i.e.Eq(18), related to the true size distribution, dependson the size distribution of the fuel fed; a narrowsize distribution gives a larger error than a wide sizedistribution, because of the overlapping of the sizedistributions of fragments.

2.1.4 Fragmentation rate constant

The fragmentation behavior during devolatilizationand char combustion differs, Chirone et al. [1991].During devolatilization, fragmentation is caused bythermal shock and gas expansion inside the particle.This relates the fragmentation rate constant to thevolume of the particle,

(21)

Af,dev is the fragmentation constant during devolati-lization. Values of the fragmentation constant can beestimated from data on the probability to fragment,the number of fragments produced from a motherparticle, and the mean diameter of fragments. Suchdata are found in the literature, e.g. Chirone et al.[1991]. The timing of fragmentation is not wellknown, but some work has been carried out, e.g.Stubington [1996], which shows a great variety oftiming depending on type of coal.

During char combustion, fragmentation is caused byirregular effects of combustion on the surface of theparticle or by collision with other solid particles,which relates the fragmentation rate constant duringchar combustion to the particle surface.

(22)

The fragmentation constant during char combustion,Af,char is assumed to be much larger than thesecondary fragmentation and analogous to theattrition rate constant found in the literature., whichmeans that the attrition rate constants found in theliterature, e.g. Arena et al. [1990] Chirone et al.[1991], can be used for the fragmentation constantduring char combustion.

2.2 Special models for CFB

In a stationary FBC all the fuel is in the bed inthe bottom part of the combustion chamber, but ina CFBC fuel and bed material are distributed in theentire combustion chamber. The size distribution andthe concentration of fuel along the riser in CFBC ismodeled here. These quatities have only a minoreffect on the fuel loading, but they affect formationand destruction of emissions.

2.2.1 Distribution of fuel along the riser

The ratio of the mass of fuel and inert material,the fuel concentration, decreases with height in theCFBC for large particles and increases for smallparticles. The velocity ratio of fuel and inert particlesbehaves like the mass ratio. Large fuel particlesare carried upwards by collision with small inertparticles. When the bed voidage becomes larger, theforce acting on the large particles decreases, and sodoes the velocity of the large particles. The smallfuel particles, having a lower slip velocity than theinert particles, experience the opposite situation; theyare held down by collisions with the inert particles.In this case the collision force decreases with largerbed voidage, and the velocity of the small particlesincreases. Assuming that, along the riser, the ratioof the mass distribution of fuel and inert material isproportional to the ratio of the velocity distributionto the power of two, an assumption which is basedon the kinetic energy of a single particle in vacuum,

(23)

hfuel is the vertical distribution of the fuel, hinert is thevertical distribution of the inert material. Ufuel is thevelocity of the fuel particles, and Uinert is the velocityof the inert particles at the height z in the combustor.The vertical solids concentration can be estimatedusing a correlation by Johnsson and Leckner [1995],and since the concentration of fuel in the particlesuspension is low, the solids concentration in thefurnace is assumed to be that of the inert material.The inert material is assumed be mono-sized anduniformly distributed over the cross-section of theriser’s core. The velocity of the inert material andof the fuel is calculated from the slip-velocity, vinert

or vfuel and the gas velocity, Ug.

(24)

The gas velocity in the core is calculated from thesuperficial gas velocity, U and the bed voidage, b,

(25)

K is the ratio of the cross-sectional area of the riserand the core. The gas velocity in the boundarylayer is assumed to be zero. The slip-velocity iscalculated from a model of Nowak et al. [1996],which is modified to be valid for all particle sizesand not just for large particles,

(26)

Aext is external surface area of fuel particles, g gasdensity, mfuel mass of the fuel particle, g gravityforce, Rinert radius of an inert particle, minert mass ofan inert particle and inert density of an inert particle.The drag coefficient CD is calculated according toKovensky [1996]

(27)

The Reynolds number is based on the slip velocityof the fuel particle. The slip velocity of the inertparticles is calculated for freely moving particles.

2.2.2 Average oxygen concentrationand bed voidage

The mass balance of char combustion is solved for anaverage oxygen concentration, CO2, and an averagebed voidage, b. Both concentration and bed voidageare averaged over the mass of fuel,

(28)

CO2m is cross-sectional time-averaged oxygenconcentration and bm voidage in the core. If thevertical distribution of the oxygen concentration isnot known, it can be represented by the averageoxygen concentration below the secondary air inlet,since nearly all fuel is located in the bottom

part. This underestimates the shrinking rate withapproximately 15% for the small particle sizes,because some of the small fuel particles is in theoxygen richer areas above the secondary air inlet.However, since the large particles include nearlyall the mass, this underestimation has only a smalleffect on the fuel loading.

3 Experimental

The measurements were carried out in Chalmers12MWth, CFBC, which is 13.5 m high and has across-section area of 2.5 m2. The ratio K of the cross-sectional area and the core area is approximately 1.3,Zhang et al. [1995].

3.1 Measurement

The fuel was bituminous coal with a knowncomposition. The measured parameters were:

1. solids vertical distribution, by pressuredifference measurement.

2. cross-sectional time-average oxygen concen-tration profile, by suction probe measure-ments at several positions in the cross-sectionand at several heights.

3. size distribution of feed fuel; samples takenfrom the fuel feeder were analyzed by sieving.

4. size distribution of char following the fluegases; samples were taken from the secondarycyclone and the bag-house filter and analysedby sieving.

5. size distribution and concentration of fuelin the furnace; samples were taken with asuction probe at the center position of thefurnace at several heights, were sieved andthe combustible content was determind onthe entire sample and on every size fractionsieved.

The analyzes of the samples taken with the suctionprobes were rough for the large fuel particles, forthe fuel particles of the size of the inert material,and for the smallest particle sizes. There were onlya few large particles present, and it was difficultto collect a representative amount of particles. Themass of fuel particles of the same size as the inertmaterial was very small compared to that of theinert particles and close to what the equipment cananalyze. The smallest particles can be attached tolarger particles, and they can be produced during thesieving procedure.

3.2 Measurement comparedwith model calculation

The fragmentation constants and the relative sizeof the char fragments can be obtained by fittingto measurements, knowing devolatilization andchar combustion constants (a,b in Eq. 1 andcorresponding for char combustion) from empiricaldata. The best fit between measured and calculatedfuel size distributions at 0.56m, 1.5m and 7.9m,and also the fuel concentration, is shown inFig. 2 yielding a fragmentation constant duringdevolatilization Af,dev=0.11, a fragmentation constantduring char combustion Af,char=3.25•10-6 and arelative radius char=0.13. These values can becompared with fragmentation data for bituminouscoal from Chirone et al. [1991], which canbe converted to fragmentation constants varyingbetween no fragmentation and 0.15 [1/s] duringdevolatilization, and between 2•10-6 and 7•10-6 [m/s]during char combustion, in a CFBC with a superficialvelocity of 6 m/s, Arena et al. [1990].

The validity of the fragmentation constants obtainedcan be discussed comparing the measured sizedistributions and concentration of fuel, with thecorresponding calculated ones if no fragmentationhad occured. Fragmentation during devolatilizationand char combustion leads to lower fuel concen-tration in the bed, but affects the size distributionof the fuel in different ways. Fragmentation duringdevolatilization controls the size distribution of thelarge particles; an increase of the fragmentationconstant decreases the number of large particlesin the bed. If no fragmentation took place duringdevolatilization, there would be a much higherconcentration of large particles than shown by themeasurement. This leads to the conclusion thatthere must have been fragmentation during thedevolatilization. The number of particles followingwith the flue gases is much larger than the number ofparticles fed to the furnace, but also much larger thanthe number of particles which could be producedfrom fragmentation during devolatilization. Thisleads to the conclusion that the particles undergofragmentation also during char combustion. Thegreat increase of the number of particles below 1mm can only be explained by fragmentation duringchar combustion. The number of small particlesalso gives an indication on the size distribution ofthe fragments produced during the char combustion,controlled in the model by the relative radius.

0.01 0.1 1 100

250

500


Fue

l mas

s p.

d.f.

[1/m

m]

0.01 0.1 1 100

250

500


Fue

l mas

s p.

d.f.

[1/m

m]

0.01 0.1 1 100

250

500


Fue

l mas

s p.

d.f.

[1/m

m]

0 5 100

0.02

0.04

0.06

Height [m]

Fue

l con

cent

ratio

n [−

]

Figure 2. Comparison between model (solid lines) and measurement (circles and stars) of the fuel massprobability density functions at 0.56m (top-left fig.), at 3.7m (top-right fig.) and at 7.9m (bottom-leftfig.) in the riser, and the fuel concentration along the riser (bottom-right fig.).

4 Result

Fuel loading and overall size distribution in an FBC,and distribution at different heights in a CFBC areaffected by the operating conditions.The followingparameters have been investigated:

1. type of fuel2. size distribution of fuel fed and fragmentation

behavior3. bed temperature4. superficial velocity5. air to fuel ratio6. pressure

To compare different operating conditions a numberof parameters has to be held constant. If nothing elseis said, the following parameters are held constant:

1. cross-sectional area2. power output3. average oxygen concentration4. average bed voidage5. superficial velocity

6. fragmentation constants and the relativeradius are those determined above

7. rate constants for devolatilization and charcombustion

8. size distribution of the fuel fed9. size distribution and amount of fuel, entrained

by the flue gases

The input data are the same as in the case analyzedabove. The fuel loading is related to this case.The fuel loading is the sum of the mass duringdevolatilization and tha mass during char combustioncalculated from Eq 8 and the mass balans Eq 12.

4.1 Influence of different fuels

The fuels considered are bituminous coal, wood-chips and peat. Fuel specific data are time ofdevolatilization, kinetics during char combustion,fuel composition and fragmentation constants. Themass of fuel fed to the combustor has to be adjustedaccording to the different heating values of the fuels.Fragmentation rate constants of peat and wood-chips has been estimated from visual observation

0.1 1 100

100

200


Mas

s p.

d.f.

[1/m

]

Coal Wood Peat0

0.5

1

Fue

l Loa

ding

[−]

Figure 3. Fuel loading relative the fuel loading of coal (left fig.) Size distribution offuel in the bed (right fig.), bituminous coal solid line, wood chips dashedline and peat dashed dotted line. N.B. the logarithmic scale.

of the combustion in a CFBC and investigation ofbed samples. The fragmentation constant duringdevolatilization is highest for peat and lowest forwood chips, the fragmentation constant during charcombustion is lowest for coal and highest for peatand wood-chips. The relative radius is assumed tobe the same for all fuels. The fuel loading and thesize distribution of fuel in the boiler are shown inFig. 3. The fuel loading is much higher for coalthan for biofuels and lowest for peat.

4.2 Influence of size distribution of fuelfed to the combustor and fragmentation

The size distribution of the inlet coal in the caseanalysed above is a mean value of several samples.To show the influence the size distribution of theinlet fuel and the fragmentation parameters on thefuel loading, the fuel loading has been calculated forthe average, the largest and the smallest particle sizedistributions of the fuel fed, Fig. 4. Fig. 4 also showsthe influence of different fragmentation parameterson the size distribution of fuel in the combustor.The fuel loading decreases rapidly with an increasein fragmentation constant during devolatilization, andthis mitigates the influence of the size distribution ofthe feed fuel. The fragmentation constant during charcombustion has a more moderate influence on thefuel loading, and it does not have the same stabilizingeffect for changes in the feed size distribution asthat during devolatilization. The relative radius hasnearly no infuence on the fuel loading but controlsthe distribution of the small particles (<1mm).

4.3 Influence of bed temperature

The time of devolatilization is approximately inverslyproportional to the bed temperature, Winter [1995].The fragmentation constant during devolatilization is

assumed to change proportional to bed temperature,since the driving force for fragmentation, the heatingrate, increases with temperature. In Fig. 5 theinfluence of bed temperature on loading and sizedistribution of fuel can be seen. An increase of thebed temperature decreases the fuel loading rapidly,and the number of small particles becomes smaller, aconcequence of the constant fragmentation constantduring char combustion. The reduction of fuelloading with increasing bed temperature is mainlydue to the increase of the surface temperature ofthe particles, which is strongly connected to the bedtemperature.

4.4 Influence of superficial velocity

The amount of air supplied to the combustor isproportional to the superficial velocity. If the averageoxygen concentration is held constant, also thefuel feed to the combustor and the power outputbecome proportional to the superficial velocity.The combustion rate is only slightly affected bythe superficial velocity in the special case of theCFBC, where the mass of fuel reaching the oxygenricher area above the secondary inlet increases withvelocity. The fragmentation rate constant duringchar combustion is usually considered proportionalto the velocity difference between the superficialvelocity and the minimum fluidization velocity.Then, the shrinking rate of fuel particles during charcombustion increases with the superficial velocity,but the reduction of fuel loading created is muchlower than the increase of the fuel loading causedby the higher input of fuel to the combustor. Fig.6 shows the influence of the superficial velocity onthe fuel loading and the fuel concentration vs heightin a CFB.

0.01 0.1 1 10 100

0

100

200

300

Diameter [mm]M

ass

p.d.

f. [

1/m

m]

γ=0.02

γ=1

0.01 0.1 1 10 100

0

100

200

300

Diameter [mm]

Mas

s p.

d.f.

[1/m

m]

kfchar=9

kfchar=0

0.01 0.1 1 10 100

0

100

200

300

Diameter [mm]

Mas

s p.

d.f.

[1/

mm

]

kfdev=0.15

kfdev=0

0 0.25 0.5 0.75 10

1

2

3

4

Relative Radius [−]

Fuel

Loa

ding

[−

]

Char Combustion

Largest size of fuel fed

Smallest size of fuel fed

0 3 6 90

1

2

3

4

Fragmentation Constant [µm/s]

Fuel

Loa

ding

[−

]

Char Combustion



0 0.05 0.1 0.150

1

2

3

4

Fragmentation Constant [1/s]

Fuel

Loa

ding

[−

]

Devolatilization



Figure 4. The top figures show the fuel loading for the three size distributions of the fuel fed and theinfluence of the fragmentation constant during devolatilization (left fig.), fragmentationconstant during char combustion (middle fig.) and relative radius (right fig.). Thebottom figures show the influence of the fragmentation constant during devolatilization(left fig.), the fragmentation constant during char combustion (middle fig.) and therelative radius (right fig.). on the size distribution of the fuel in the combustor.

1000 1100 12000

0.5

1

1.5

Temperature [K]

Fue

l Loa

ding

[−]

0.01 0.1 1 10 100

0

100

200

Diameter [mm]

Mas

s p.

d.f.

[1/m

]

T=1023K

T=1223K

Figure 5. Fuel loading vs bed temperature (left fig.) Size distribution of fuel in thebed for different bed temperatures (right fig.)

4.5 Influence of the air to fuel ratio

The average oxygen concentration is proportionalto the air to fuel ratio. The influence of thestoichiometric air to fuel ratio on the fuel loading and

the fuel size distribution is shown in Fig. 7. A risein this ratio increases the shrinking rate during charcombustion somewhat more than the proportionalincrease of the average oxygen concentration. Theamount of small particles will be reduced accordingly

0 5 100

0.02

0.04

Height [m]

Fue

l Con

cent

ratio

n [−

]

0 5 100

0.5

1

1.5

Superficial Velocity [m/s]

Fue

l Loa

ding

[−]

10 m/s

6 m/s

3.5 m/s

Figure 6. Fuel loading vs superficial velocity (left fig.). Fuel concentration along the combustor (right fig.).

1 1.2 1.40

0.5

1

1.5

2

Air to Fuel Ratio [−]

Fue

l Loa

ding

[−]

0.01 0.1 1 10 1000

100

200

Diameter [mm]

Mas

s p.

d.f.

[1/m

]

Air/Fuel 1.05

Air/Fuel 1.5

Figure 7. Fuel loading vs air to fuel ratio (left fig.). Size distribution of fuelin the bed for different air to fuel ratios (right fig.)

and for the same reason as during an increase of bedtemperature. The attrition rate constant increaseswith a rise in the oxygen concentration to someextent, Chirone et al. [1991], but here it is keptconstant. Most significant is that no attrition occursif the oxygen concentration is close to zero.

4.6 Influence of pressure

If a first order reaction is assumed, the surfacereaction rate constant, kc, is independent of pressure.This assumption can be questioned, and in recentworks of Essenhigh [1996] and Croiset et al. [1996]there is some pressure dependence on the surfacereaction rate constant. The pressure dependence onthe mass transfer coefficient is different for smalland large particles, caused by the correlation ofSherwood’s number, Eq. (15). For small particlesSherwood’s number is nearly constant, and for largeparticles it is proportional to the square root ofReynold’s number. The kinematic viscosity andthe molecular diffusivity are inversely proportionalto pressure, and the slip velocity is only slightlyaffected by the pressure, due to a change in thedrag force. This makes the mass transfer coefficient,

, inversely proportional to pressure for small

particles and inversely proportional to the squareroot of the pressure for large particles. If the airto fuel ratio and the superficial velocity are keptconstant, then the mass of the fuel fed to thecombustor, the power output and the average oxygenconcentration are proportional to the total pressure.For kinetially controlled combustion, Eq. (14) showsthat the shrinking rate (dR/dt) increases linearly withpressure. When diffusion dominates, the shrinkingrate becomes independent of pressure. Only for largeparticles there is a square root dependence causedby the Reynold’s number. For the size distributionconsidered these relationships give an increase of theshrinking rate, but due to the condition of constantair to fuel ratio and superficial velocity, the fuelloading increases as a consequence of the fuel feedrate being proportional to pressure. The resultingfuel loading and size distribution of fuel at differentpressures are shown in Fig. 8. With the present sizedistribution the fuel loading increases with pressureto the power of 0.7, and the overall shrinking ratebecomes proportional to the pressure to the power of0.3, the shrinking rate being controlled by diffusion.The number of small particles becomes smaller withthe rise of pressure, a consequence of the constantfragmentation constant.

0.01 0.1 1 10 1000

100

200

Diameter [mm]

Mas

s p.

d.f.

[1/m

]

1 bar

20 bar

0 10 200

5

10

Pressure [bar]

Fue

l Loa

ding

[−]

Figure 8. Fuel loading vs pressure (left fig.) Size distribution of fuel in the bed at different pressures (right fig.)

5 Conclusions

A general model of fuel loading and size distributionof fuel in an FBC has been developed. For CFBCthe fuel concentration and the size distribution alongthe riser are also modeled. The fragmentationis to some extent treated in a new way, andthe fragmentation rate constants obtained fromevaluation of experimental data show a goodagreement with rate constants estimated fromliterature data. The model includes the mostimportant influencing parameters and has a shortcalculation time. (30 sec on a SUN Ultra).

The fuel loading depends on type and size of fuel,fragmentation and pressure; all these parametershave a great influence on the combustion. A riseof pressure and/or superficial velocity increases thepower output from the combustor, and also the fuelloading. Bed temperature and air to fuel ratio havealso an influence on the fuel loading, but not asgreat as the other parameters investigated. The sizedistribution of fuel in the bed is mostly dependent onthe fragmentation behavior of the fuel. For CFBC,the variation of fuel concentration along the riser ismainly affected by the superficial velocity.

Acknowledgments

This work was supported by a scholarship from theNordic Energy Research Program for Combustionof Solid Fuels and the Swedish National Board forIndustrial and Technical Development (NUTEK).

7 Nomenclature

Af,dev [1/s] Fragmentation constantduring devolatilization

Af,char [m/s] Fragmentation constantduring char combastion

Aext [m2] Surface area of a fuelparticle

a,b Fuel dependent constantsCO2 [mol/m3] Oxygen concentrationCD Drag force coefficientDO2 [m2/s] Molecular diffusivity of O2F [kg/s] Mass flowg [m/s2] GravityHc [J/kg] Heat valueh Size distributionK Area ratio of cross-section

and corek [m/s] or

[1/s]rate constant

M [kg] Total massMc [kg/mol] Molecular mass of carbonm [kg] Mass of a single particleP Fragmentation probabilityR [m] Particle radiusRe Reynolds numberSc Schmidt numberSh Sherwood numbertd [s] Time for devolatilizationU [m/s] Superficial velocity or

velocityx Relative volatile contentVdev Initial volatile contentv [m/s] Slip velocityy [m] Radius of fragment

Greek letters

[W/m2

K]Heat transfer coefficient

[m/s] Mass transfer coefficientRelative fragment size

b Bed voidage[kg/m3] Density

Scale factor[s] Time for which a particle

been subjected todevolatilizationSplit factor of CO and CO2

Index

ash Char leaving with flue gasesc Carbonchar Char or during char

combustion

dev Volatiles or duringdevolatilization

f Fragmentsfuel Fuelg Gasinert Inert materialmax Largestn Number basesr Radiationtot Total0 Initial1 During devolatilization2 During char combustion

8 ReferencesArena, U., Cammarota, A., Chirone, R.,Massimilla, L., Siciliano, L., Basu, P., CarbonAttrition During the Combustion of a Char in aCirculating Fluidized Bed, Combust. Sci. andTech., 73, 383-394, (1990).

Arena, U., Chirone, R., D’Amore , M., MiccioM., Siciliano, L., Some Issues in ModellingBubbling and Circulating Fluidized Bed CoalCombustors, Powder Technology, 82, 301-316,(1995)

Arthur, J.R., Reactions between Carbon andOxygen, Trans.Faraday Soc., 47, 164, (1951).

Chern, J-S., Hayhurst, A.N., The Extent ofFragmentation of Various Coals during theirPyrolysis in a Hot Fluidized Bed, Joint Meetingof the Portuguese, British and Swedish Sectionsof the The Combustion Institute, Funchal,Madeira, April, (1996).

Chirone, R., Salatino, P., Massimilla, L.,Comminution of Carbons in Fluidized BedCombustion, Prog. Energy Combust. Sci, 17,297-326 (1991).

Croiset, E., Chantal, M,. Rouan, J.P., Richard,J-R., The Influence of Pressure on CharCombustion Kinetics, 26th Symp.(Int.) onCombustion, Combustion Institute, Pittsburgh,(1996).

Essenhigh, R.H., Influence of Pressure on theCombustion Rate of Carbon, 26th Symp.(Int.) onCombustion, Combustion Institute, Pittsburgh(1996).

Halder P.K., Basu P., Mass Transfer from aCoarse Particle to a Fast Bed of Fine Solids,A.I.Ch.E. Symp. Ser No. 262., Vol. 84, pp.58-64, (1988)

Johnsson F., Leckner B,. Vertical Distribution ofSolids in a CFB Furnace, Proceedings of theThirteenth International Conferance on FluidizedBed Combustion, Ed. K.J., Heinschel, ASME,New York, pp 671-679, (1995)

Kunii D., Levenspiel O., FluidizationEngineering, John Wiley & Sons, New York,(1969)

Kovensky, V.I., Account for the Constraining ofParticle Motion in the Freeboard, Presented at theInt. Workshop on the INTAS project No.94-4313,Chalmers University of Technology Gothenburg,(1996).

Nowak, W., Bis, Z., Gajewski, W., Matsuda, H.,Hasatani, M., Carryover of Coarse Particles froma Dense Bed in a Multy-Solid Fluidized Bed,Preprints of the 5th Int.Conf. on CFB, Beijing, P.DGS11, (1996).

Salatino, P., Massimilla, L., A Predictive Modelof Carbon Attrition in Fluidized Bed Combustionand Gasification of a Graphite, Chem. Eng. Sci.,44, 1091-1099, (1989).

Sasongko, D., Stubington, J.F., SignificantFactors Affecting Decolatilization of nonFragmenting, non Swelling Coals in FluidizedBed Combustion, Chem. Eng. Science, 51,3909-3918, (1996).

Stanmore B.R., Brillard, A., Gilot, P., Delfosse,L., Fragmentation of Small Particles underFluidized Bed Combustor Conditions, 26thSymp.(Int.) on Combustion, CombustionInstitute, Pittsburgh, (1996).

Winter. F., Single Fuel Particle and NOx/N2O-Emission Characteristics under (Circulating)Fluidized Bed Combustor Conditions, Ph.D.Thesis, University of Technology, Vienna, (1995).

Zhang, J.Q., Devolatilization an Combustion ofLarge Coal Particles in Fluidized Sand Beds,Technical Report QFBC.TR.87.2, Queen’sFluidized Bed Combustion Laboratory, (1987).

Zhang, W., Johnsson, F., Leckner, B.,Characteristics of the Lateral Particle Distributionin Circulating Fluidized Bed Boilers, 4thInt.Conf. on CFB Technology, Ed. A.A.Avidan,AIChE, Hidden Valley, (1994), 266.

Appendix A: Fragmentation

A.1 Fragmentation during devolatilization of particles of a single size

During devolatilization fuel particles fall apart due to fragmentation. Thefragmentation appears at different times for the feed particles, the principlebehavior is shown in Fig. A1. A number of particles of a certain size is feed tothe devolatilization process. After a time t1 one of the particles fragments, andthe total mass decreases with the mass of one particle, at t2 another particlefragments, and the total mass of the particle size drops again, and so on.

If the number of particles of a single size is large, the mass of the particle sizecan be treated as a continuous mass, and the mass loss can be described as:

dM(t)

dt= f(t)M(t) f(t) = (dM(t)=dt)=M(t) (A 4)

M is the mass of a feed particle size, t is the time which a particle has beensubjected to devolatilization and f(t) is a fragmentation rate function. The sameexample as in Fig. A1 is shown in Fig. A2 for a continuous mass instead ofsingle particles.

Assuming steady state conditions, the mass during devolatilization is given bythe mass flow, F:

F = M=t (A 5)

Rewriting Eq. A4 for the mass flow of a single particle size:

ttd0 t1 t2 t3

M

0 t1 t2 t3

ttd

Figure A 1. Principle fragmentation behavior of a group of particles havingduring devolatilization a certain size. M is total mass of the particlesize, t is time and td is time of devolatilization. In this figure themass loss due to the volatile release is not considered.

I

dF (R; t)

dt= f(R; t)F (R; t) F (R; t) = F0(R) exp( f(R; t)dt) (A 6)

F0 is the initial mass flow. The fragmentation rate function f(R,t) can beestimated from measurements, or it can be estimated from assumptions ofthe fragmentation behavior. The simplest assumption is that the fragmentationrate is independent of particle size and time:

f(R; t) = kf;dev (A 7)

The fragmentation on a number basis is then proportional to the particle volume.For instance, for a spherical particle of the size R1 the probability to fragmentat a given time compared with a smaller particle of size R2 becomes equalto (R1/R2)3.

Another simple assumption is that the fragmentation rate is independent of time,but dependent of size. Assuming that the pressure built up inside the particlecan be modeled by a gas dome, a raise of temperature increases the pressureinside the dome and increases the stresses in the dome walls. The stressesin the wall of a gas dome is proportional to the ratio of the volume and thesurface area, which means that the stresses in the dome wall is proportional

0

td

t0 > t > td

M(t)M(0) M(td)

Mfrag (t)

M

t

f(t)

ttd

td

0 0Figur A 2. Principle fragmentation behavior of the mass of a single

particle size during devolatilization. In this figure the massloss due to the volatile release is not considered.

II

to the dome radius. The fragmentation rate assumed to be proportional to thesurface stresses:

f(R; t) = kf;dev R (A 8)

The fragmentation rate can also be assumed to be time dependent, for example:it may take some time before the fragmentation starts, and after a certain timethe fragmentation stops. This can be modelled by spliting up the fragmentationrate function in steps:

f(R; t) =

kf;dev 1 f(R) 0 < t t1kf;dev 2 f(R) t1 < t t2kf;dev n f(R) tn < t td

(A 9)

The model assumes that a separation of devolatilization and char combustionis possible. The particle size is related to the feed particle size and not to theactual size during devolatilization, which makes it possible to model fuels whichchange size during devolatilization, due to shrinking or swelling.

In the literature there are data on the probability to fragment for different fuelsand particle sizes. These data can be used to estimate the fragmentationrate function f(R,t). The probability to fragment is the ratio of the mass of thefragments and the mass of fuel after devolatilization if no fragmentation hadoccurred:

Pf;dev(R) =

F0(R)exp(0) F0(R)exptd

0

f(R; t)dt

F0(R)exp(0)= 1 exp

td

0

f(R; t)dt

(A 10)

A.2 Fragmentation during char combustion

Fragmentation during char combustion differs fundamentally from fragmentationduring devolatilization; during devolatilization the fragmentation is caused mainlyby gas expansion and thermal decomposition inside the fuel particle, but duringchar combustion the fragmentation is caused mainly by particle collision andirregular combustion on the particle’s surface, Fig. A3. The different sizes of thefragments during char combustion make it convenient to split up the fragmentsinto different categories and relate them to the origin. The fine fragmentscaused by the collisions between bed particles and fuel particles are producedby attrition, and the coarser fragments are caused by irregular combustion on thefuel particle’s surface, making the particle fall apart into larger pieces. The lattertype is called secondary fragmentation. Other suggestions are also present inthe literature. In this work the mass loss due to fragmentation is treated with

III

a single reaction rate, related to the surface area, Aext, and the slip velocitybetween bed particles and fuel particle, Us:

dM

dt= M kf;char(Aext; Us) (A 11)

The fragment sizes are estimated by an size distribution.

A.3 Distribution of fragments

It is assumed that the fragment of a particle also can fragment, and thedistribution of particle sizes can have been formed during several steps offragmentation. Here the size distribution of a single fragmentation step istreated, the primary fragmentation. The primary distribution of fragments isnot known, but experimental results on the size distribution after devolatilizationand during char combustion are available in the literature for some fuels. If thereis a large number of particles with different sizes, the primary distribution canbe modelled by a fictitious distribution, which describes the size distributionafter devolatilization and during char combustion. The primary distributionof fragments on a number basis is assumed to follow a first order gammadistribution:

g(y) =exp ( y=)

y 0 (A 12)

where y is the radius of the fragments and is a scale factor. The boundarycondition of a gamma distribution is that g(y) has a value between zero andinfinity, but the maximum size of the fragments is limited to the size of thefragmenting particle, ymax. This makes it necessary to normalize the gammadistribution:

Irregular combustionAttrition

products

Secondary Fragmentation

Fuel Particle

Bed Particles

BedParticle

Figur A 3. Fragmentation during char combustion

IV

gn(y) =exp( y=)

ymax

0

exp( y=)dy=

exp( y=)

1=(1 exp( ymax=))(A 13)

The scale factor gives the shape of the distribution and the location of the meanradius. It is assumed that the relative location of the mean radius is at the samerelative radius, , for all particle sizes. Defining the relative radius as the ratio ofthe mean radius of the non-normalized distribution, ymean, and the fragmentingparticle size, yields:

= ymean=ymax

ymean =

= ymax

(A 14)

By changing the value of the relative radius, the distribution gn(y) is changed,and different fragmentation behaviors can be modelled, see Fig. A4. A smallrelative radius produces many small fragments and few large fragments. If therelative radius is large the distribution becomes uniform, which can be shown byan expansion of the first order gamma distribution to a power series

exp ( y=)

=

1

1 + ( y=) +

( y=)2

2!+

( y=)3

3!+ +

( y=)n

n!+

(A 15)

The ratio y/ is much smaller than 1, if the relative radius is large, and thismake the distribution uniform:

Const

ymax

0

1

dy = Const

ymax

(A 16)

This gives

Const =

ymax

g(y) =1

ymax

(A 17)

The model is not based on single particles. It is based on the mass of a largenumber of particles and the distribution on a mass basis is more interestingthan the distribution on a number basis. If the fragments are assumed to bespherical, the mass can be related to a particle radius:

m =4y3%

3(A 18)

If all fragments have the same density, the mass distribution is given by themass multiplied with the number of fragments of a given size:

V

hm(y) = mN g(y) =4y3%

3Nexp( y=)

= Const

y3exp( y=)

(A 19)

N is the average number of fragments produced from a fragmenting particle.For the probability density function, p.d.f, of the mass distribution of fragmentsthe constant Const becomes:

Const

1

0

y3 exp ( y=)

dy = Const 63 62y 3y2 y3 exp ( y=)

1

0=

= Const 63 = 1(A 20)

This gives

Const =1

63(A 21)

The Const inserted into Eq. A19 converts the p.d.f of the mass of fragmentsinto a fourth order gamma distribution:

h(y) =y3 exp ( y=)

64(A 22)

In the same way as the distribution of the number of fragments the massdistribution is limited for particle sizes between zero and ymax, which makes itnecessary to normalize also the mass distribution:

yymax

γ

gn

Large γ Small γ

Figur A 4. The influence of the relative radius, , onthe distribution of the fragments

VI

yymax

γhn Small Large

Figur A 5. The influence of the relative radius on themass distribution of fragments

hn(y) =y3exp( y=)

ymax

0

y3exp( y=)dy(A 23)

the scale factor of the mass distribution is:

ymean = 4

= ymax=4(A 24)

and for large relative radii the mass distribution becomes:

hn(y) =4 y3

y4max

(A 25)

The influence of the relative radius on the mass distribution can be seen inFig. A5

Appendix B: Devolatilization

The devolatilization is modeled by the assumption of a shrinking core, see Fig.A6, and the time of devolatilization is modeled by the correlation:

td = aRb (A 26)

Assume that the remaining devolatilization time t for a particle with the coreradius r can be modeled with the same correlation:

t = arb (A 27)

VII

Rr

Char residue

Devolatilization front

Figur A 6. Shrinking core assumption

A relative volatile content x is defined as the ratio of the mass of the remainingvolatiles and the initial volatiles:

x =

Remaining mass of volatiles

m m0(1 Vdev)

m0Vdev

Initial mass of volatiles

=r

R

3

=t

td

3=b

(A 28)

The time during which a particle has been subjected to devolatilization, , is:

= td t (A 29)

and the relative volatile content expressed as a function of the time is:

x =td

td

3=b

= 1

td

3=b

(A 30)

The mass of a single particle mass at time is:

m = m0(1 Vdev)

Char

+m0Vdevx()

V olatiles

= m0(1 Vdev(1 x())) (A 31)

For a steady state flow of fuel particles, feed to the devolatilization process themass flow at a given time is:

F = F0(1 Vdev(1 x())) (A 32)

This expresses the mass flow of a fuel which does not fragment duringdevolatilization.

Appendix C: Simultaneous fragmentation andvolatile release during devolatilization

VIII

C.1 A single particle size

Fragmentation means that particles fall apart into smaller particles, but duringthe devolatilization the mass decreases also due to the reduction of fuel densitycaused by the volatile release. This makes it necessary to compensate the“initial” mass flow in Eq. A6 in Appendix A for the density reduction Eq. A32in Appendix B:

F (R; ) = F0(R) (1 Vdev(1 x(R; )))

V olatile release

exp( f(R; )d)

Fragmentation

(A 33)

The total mass of a particle size is given by integration of the mass flow overthe time of devolatilization:

Mdev(R) =

td

0

F (R; ) d (A 34)

The mass of char of the fragments is the difference between the char feed tothe devolatilization process and the char of size R leaving the devolatilizationfor char combustion:

Ffp;char(R) = F0(R)(1 Vdev)

Feed char

F0(R)(1 Vdev)exptd

0f(R; )d

Char after devlotilization

= F0(R)(1 Vdev) 1 exp

td

0f(R; )d

(A 35)

The mass of volatiles in the fragments is the difference between the volatiles fedto the devolatilization process and the volatiles leaving due to volatile release.The change of the mass flow is due to the mass reduction due to fragmentationand volatile release. When a derivation of Eq. A33 is done, the fragmentationand the volatile release are separated from each-other:

F (R; ) = F0(R)g(R; )h(R; )

g(R; ) = 1 Vdev(1 x(R; ))

h(R; ) = exp( f(R; )d )

(A 36)

and the derivative becomes:

F0(R; ) = F0(R) g

0(R; )h(R; )

V olatile release

+ g(R; )h0(R; )

Fragmentation

(A 37)

IX

where the primes denote derivatives. By integration of the volatile release overthe time for devolatilization, the mass flow of volatiles leaving the particle sizecan be calculated. If the initial mass flow of volatiles is subtracted from the massflow of volatiles leaving the particle size during devolatilization, the mass flowof volatiles in the fragments is achieved:

Ffp;vol(R) = F0(R) Vdev +td

0g0(R; )h(R; )d (A 38)

The plus sign is caused by the integration of the volatile release over time whichturns out to be negative.

C.2 The size distribution of fuel particles

In a size distribution of fuel particles the model formulated for a single particlesize corresponds to the largest particle size in the distribution; all other particlesizes will get a contribution of particles in form of fragments. If all fragmentshave the same relative volatile content as the fragmented particle, the fragmentsenter the corresponding particle size element having different relative volatilecontents. For example, in Fig. A7, a particle of size R1 starts being devolatiles.After a time t1 the particle disintegrates into two pieces, one of the size R2 andone of the size R5. Both pieces are assumed to be spherical and have the samerelative volatile content x1. After a time t2 the particle of size R2 falls into twopieces of the sizes R3 and R4, and both are assumed to have the same relativevolatile content x2. The time t1 represents the time for a particle of size R1 torelease volatiles corresponding to the relative volatile decrease 1–x1. t2 is thetime during which a particle of size R2 releases volatiles corresponding to therelative volatile decrease x1–x2, and so on. With the assumption made above,the devolatilization process will be faster for a particle which fragments comparedwith a particle which does not fragment. This time reduction is strongly connectedto the fragmentation behavior, e.g. if the particle falls apart into a large number ofparticles of approximately the same size in the beginning of the devolatilization,the time reduction will be significant, but if the particles fall apart in one largeparticle and a few small particles in the beginning of the devolatilization or in alarge number of particles in the end of the devolatilization, then the reduction ofthe devolatilization time will be small. To calculate the mass of a particle size,which is continuously fed with particles of different relative volatile content, itis necessary to build up a two-dimensional distribution of fragments, where themass of the fragments is a function of relative volatile content and particle size.This is possible, but the calculation becomes both memory and time consuming.A faster way is to average the relative volatile content of all particles fed toone particle size. As shown above the total mass of volatiles and char in thefragments from one particle size are calculated in a rather simple way, and ifthe distribution of the fragments hn(y,R) is known, the mass of volatile and charfed to a particle size y from a larger particle size R becomes:

X

Ff;char(R; y) = Ffp;char(R)hn(y; R)

Ff;vol(R; y) = Ffp;vol(R)hn(y; R)(A 39)

and the mass of volatiles and char from all larger particle sizes R>y are:

Ff;char(y) =

Rmax

y+

Ffp;char(R)hn(y; R) dR

Ff;vol(y) =

Rmax

y+

Ffp;vol(R)hn(y; R) dR

(A 40)

The average relative volatile content in the fuel fed to a particle size, x0, is then:

x0(y) =

Mass of volatiles fed to a particle size

F0(y)Vdev + Ff;vol(y)

F0(y)(1 Vdev) + Ff;char(y)Vdev

1 Vdev

Initial volatile mass related to the mass of char fed to a particle size

(A 41)

When the average relative volatile content in the fuel fed to a particle size is lessthan one, a compensation of the initial mass in Eq. A33 must be done. Thiscompensation is done by the introduction of a fictitious initial mass flow basedon the initial mass flow of char fed to a particle size, F0,char:

F0;char(y) = F0(y)(1 Vdev) + Ff;char(y) (A 42)

The mass of char is only affected by fragmentation, and at (x0) the mass flowof char is the same as the initial mass flow of char. The fictitious char massflow, F*

0,char, is then the corresponding mass flow at time zero:

F

0;char(y) = F0;char(y)=exp(x0(y))

0f(; y)d (A 43)

and the fictitious initial mass flow, F0* of fuel at time zero is:

F

0 (y) = F

0;char(y)=(1 Vdev) (A 44)

The equations for a single particle size, Eq. A33–A35 and A38, can then berewritten for a size distribution and the mass flow becomes:

F (y; ) = F

0 (y) (1 Vdev(1 x(y; )))

V olatile release

exp( f(y; )d)

Fragmentation

(A 45)

XI

The corresponding total mass is:

Mdev =

0

Rmax

td

(x0)

F (y; ) ddy (A 46)

The mass of char in the fragments:

Ffp;char(y) = F0;char(y) 1 exp

td

(x0)

f(y; )d (A 47)

and the mass of volatiles in the fragments:

Ffp;vol(y) = F0(y)Vdev + F0;vol(y) +td

0F

0 (y)g0(y; )h(y; )d (A 48)

The averaging of the relative volatile content produces an error, which is small(0–5 %) in most cases. When the fragmentation rate function is assumed tofollow Eq. A7 the error is less than 2%. When a time dependence is assumed onthe fragmentation rate function, e.g. Eq. A9, this error can become unacceptablylarge. The worst case if the fragmentation is takes place only at the very endof the devolatilization period, when the error can be around 30%. To keep thiserror at an acceptable level, the devolatilization can be split up into several stepsrelated to the relative volatile content. For example, if all fragmentation occursbetween a relative volatile content of x1 and 0, then the devolatilization can besplit up into two steps, one for the relative volatile content between 1 and x1,and one between x1 and 0.

The relative volatile content in the fragments can be modelled by two extremecases: one is the one described above Fig. A7, where all fragments have thesame volatile content, and the other is that the char layer falls of the shrinkingcore as illustrated in Fig. 8. A particle of size R1 starts devolatilization. After a

1 0x

R1

R2

R3

R4

R5

t1

t2

t5

t4

t3

x1 x2

τ

R

t1

t2

t3

t4t5

t0 t0

Figur A 7. Time for devolatilization of a fragmenting particle

XII

1 0x

R1

R2

R3R4R5

t1

t2

t3

x1 x2

τ

R

t1

t2

t3

t0 t0

Figur A 8. Time for devolatilization of a particle who the char layer falls of the core

time t1 the particle disintegrates into two pieces, one piece of size R2 originatesfrom the core and the other piece of size R5 originates from the char layer.The particle which consists of char goes directly to char combustion. After atime t2 the same procedure is repeated and the core forms a particle of sizeR3 and the char layer leaves with a particle of size R4. In this extreme casethe devolatilization time is independent of the fragmentation. To model this, twomass distributions of the fragments have to be assumed, one for the distributionof the cores, hcore and a second for the distribution of the char fragments, hf,char.The mass of the fragments, including the core, which is feed to a particle sizecan be calculated from the volatiles in the fragments:

Fcore(y) =1

Vdev

Rmax

y+

hcore(R)Ffp;vol(y; R)dR (A 49)

and the mass of the fragments including the char of a particle of size R leavingthe devolatilization for the char combustion is:

Ff;char(y) =

Rmax

y+

hf;char(R)Ffp;char(y; R)dR Fcore(y)(1 Vdev) (A 50)

The devolatilization can then be calculated as for a single particle, with the initialmass flow compensated with the mass flow of the core fragments, and the charleaving for char combustion compensated with the mass flow of char fragments.

XIII

Appendix D: Char burning as shrinking spheres

The mass reduction of a single particle during char combustion can be expressedas a function of external surface area, Aext, a mass transfer coefficient, , areaction rate constant, kc, an oxygen concentration CO2 and a split factor, ,the molar ratio of C and O2:

dmcarbon

dt= f(Aext; ; kc; CO2; ) (A 51)

Assuming spherical particles, the mass of the particles can be related to particleradius

mchar =4%charR

3

3(A 52)

By defining the density of the carbon in the char as

%carbon = %char %ash (A 53)

the mass of carbon in the particle can be expressed:

mcarbon =4%carbonR

3

3(A 54)

If the density is constant during char combustion, the mass reduction is onlycaused by a change of the radius:

dmcarbon

dt=

4%carbon3

dR3

dt(A 55)

dR3/dt can be expressed as dR/dt:

dR3

dt=

dR3

dR

dR

dt(A 56)

where dR3/dR is:

dR3

dR= lim

dR!0

R3 (R + dR)3

R (R + dR)= 3R2 (A 57)

Putting Eq. A56 and A57 into Eq. A55 yields:

dmcarbon

dt= 4%carbonR

2dR

dt(A 58)

This corresponds to the mass loss of a single particle, but in a combustor thereis a mass loss of a collection of particles of the same size:

XIV

dM

dt= N

dmchar

dt= N

%char

%carbon

dmcarbon

dt=

M

mchar

%char

%carbon4%carbonR

2dR

dt=

=M

4%charR3

3

%char

%carbon4%carbonR

2dR

dt=

3M

R

dR

dt(A 59)

M is the mass and N is the number of char particles of a certain particle size.

The mass reduction for a small particle is controlled by the kinetics of the surfacereaction, which can be calculated from a reaction rate constant, kc. The reactionrate constant is defined in different ways in the literature. The most commonand simple definition is that the reaction rate constant is related to the partialpressure, PO2inf or to the concentration, CO2inf, of oxygen in the bulk and thereaction is assumed to be of first order. For a shrinking sphere model the massdecrease is related to surface area:

dm

dt= AextPO2infk

c1 = AextCO2infRTk

c1 = AextCO2infk

c(A 60)

T is the surface temperature and R* is the gas constant. This gives the reactionrate constant k*

c the unit [m kgcarbon/ mol(O2) s]. In order to relate the reactionrate to the mass transfer coefficient of oxygen into the particle, the reaction rateconstant has to have the unit [m/s]. This can achieved by separation of therelation between mass of carbon and mol of oxygen from the reaction rate:

kc

= MC kcm kgcarbon

molO2 s= molcarbon

molO2

kgcarbon

molcarbon

m

s

(A 61)

Putting Eq. A61 into Eq. A60:

dmcarbon

dt= AextMCCO2infkc (A 62)

The mass reduction of a large particle is controlled by the diffusion of oxygen intothe particle’s surface which can be calculated from the mass transfer coefficient,. When the combustion follows a shrinking sphere model and is controlled bydiffusion, the oxygen concentration at the surface is much smaller than in thebulk, and the difference in the oxygen concentration between bulk and particlesurface is approximately the same as the oxygen concentration in the bulk.

dmcarbon

dt= AextMc CO2inf CO2s AextMcCO2inf

(A 63)

The simplest and most usual way to relate the mass transfer and the reactionrate to each-other, is to treat them as two parallel oxygen resistances and callthe resulting resistance apparent reaction rate, kapp:

XV

kapp =1

1 + k1c

(A 64)

The mass reduction expressed with the apparent reaction rate is:

dmcarbon

dt= AextMcCO2infkapp (A 65)

By inserting Eq. A58 into Eq. A65, the mass reduction can be related to theshrinking rate of the particle, :

4%carbonR2dR

dt=

Aext

4R2 McCO2infkappdR

dt=

McCO2infkapp

%carbon(A 66)

Appendix E: Determination of fragmentation ratesfrom data in literature or from experiments

E.1 Fragmentation during devolatilization

Measurements of the fragmentation during devolatilization is presented in theliterature in many different ways, dependent on the type of experiment performed.The most common way is to estimate the average number of particles producedfrom a fragmenting particle of a given size, often together with a mean size of thefragments. For some fuels these data are complemented with data on probabilityto fragment or/and size distribution of the fragments after devolatilization. Insome rare cases an estimation on the timing of the fragmentation is made. Mostexperiments are carried out for coals, which show large variety in fragmentationbehavior. Common for nearly all coals is that they produce a countable amountof fragments, which means that the particle falls apart in rather few largepieces. This corresponds to a large value of the relative radius and makes theprimary fragmentation follow Eq. A25. The reaction rate function, f(R,t), hasto be assumed. If there are data available on the timing of the fragmentationthese data can support the choice of a fragmentation rate function f(R,t). Thefragmentation rate, kf,dev, can be estimated by fitting the calculated, Eq. A10,to the measured probability to fragment. The fragmentation rate can also beestimated from the number of particles produced and the mean size of fragmentsafter devolatilization. The number of particles produced from one particle of theoriginal size R, Nf, can be calculated:

XVI

Nf =mo

F0

1=Number of particles

feed to devolatilization

per second

R

0

3

4%chary3

Mass of one

char particle

F (y; td)

mass per second of particles

leaving devolatilization

dy

Number of particles per second leaving devolatilization

(A 67)

Eq. A67 reveals the weakness in the use of the number of fragments; even ifthe mass of the small particles is negligible, the number of these particles canbe in majority. This means that the average number of particles produced froma particle of a given size R presented in the literature must be related to thepossibility to collect particles of the smallest particle sizes in the experimentsperformed.

For example:

Chern et al. [1996] reported that for coal particles of an initial mass of 2g,corresponding to a particle radius of about 7.5 mm, less then 5% of the masswas found in fragments having a particle radius smaller than 1.5mm. For mostfuels the average number of fragments after devolatilization was between 1 and10. Assume that the fuel does not swell and that an average of 10 particleswith a particle radius larger than 1.5mm is produced during devolatilization. Acalculation with the fragmentation rate function following Eq. A7 and with afragmentation rate, kf,dev, equal to 0.035 1/s, gives 10 particles with a particleradius larger than 1.5mm. These 10 particles corresponds to 97% of the mass,but the total number of particles given by Eq. A67 is 25. So 60% of the particlescorresponds to 3% of the mass. Fig A9 shows the calculated cumulativedistribution of mass and number of particles after devolatilization in the exampleabove.

The conclusion is that the number of particles produced from a particle of sizeR, reported from experiments, does not give sufficient information, if it is notcomplemented with the mass loss and the smallest size of the collected particles.

E.2 Fragmentation during char combustion

During char combustion fragmentation is caused by attrition and secondaryfragmentation. Values on the attrition rate during char combustion in a CFBCare given by Arena et al. [1990]. Attrition rates for BFBC conditions havebeen reported in several works, e.g. Chirone [1991], Brown et al. [1992]. Allthese works use a dimensionless attrition rate constant, katt, which gives thefragmentation rate during char combustion, kf,char, according to:

XVII

0 3 6 9 12 150

0.2

0.4

0.6

0.8

1

Diameter [mm]C

umul

ativ

e fr

actio

n

mass

num. of part.

Figur A 9. Illustration of the cumulated mass and number of particle fraction ofparticles leaving the devolatilization for char combustion

dMf (R)

dt=

katt U Umf

2RM(R)

kf;char =katt U Umf

2R

(A 68)

U is the superficial velocity and Umf is the minimum fluidization velocity. For aCFBC katt is in the range of 0.1•10- 6 to 0.7•10- 6. The mass distribution of thefragments is controlled by the relative radius. The value of the relative radiusis small (0 < < 0.05) if only attrition occur and large (0.5 < < 1) if onlysecondary fragmentation occur. In the mass balance given by Salatino [1989],which is an extension of the mass balance presented by Kunii and Levenspiel[1969], the fragments leaving a particle size element centered at R are onlyrelated to the secondary fragmentation:

0 = Fchar(R)dRd

dR

dR

dt(R)Mcharhchar(R) Fash(R)dR

Mcharhchar(R)3

R

dR

dt(R)dR + Ff2;char(R)dR Mcharhchar(R)kf;char(R)

dMf=dt

dR

(A 69)

If there is only attrition, the size reduction, which makes the particle go from onesize to another, will be affected and the shrinking rate due to char combustionhas to be complemented with a shrinking rate due to attrition:

XVIII

0 = Fchar(R)dRd

dR

dR

dt(R) +

dRf

dt(R) Mcharhchar(R) Fash(R)dR

Mcharhchar(R)3

R

dR


dMf=dt

dR

(A 70)

Index f indicates the size reduction due to attrition. The size reduction due toattrition can be calculated from the fragmentation rate:

dMf (R)

dt=

3Mf (R)

R

dRf

dt= kf;charMf (R)

dRf

dt= kf;char

R

3

(A 71)

In order to handle the attrition and secondary fragmentation simultaneously, thetwo extreme cases have to be combined in some way. In the calculation made,the extra size reduction rate due to attrition was assumed to have only a minoreffect on the total mass and on the mass distribution, and Eq. A69 was thereforeused. This assumption overestimates the total mass. In the cases calculatedthe overestimation was less than 5 %. A better way is to connect a split factor,, to the relative radius

0 = Fchar(R)dRd

dR

dR

dt(R) +

dRf

dt(R) Mcharhchar(R) Fash(R)dR

Mcharhchar(R)3

R

dR


dMf=dt

dR

(A 72)

A large relative radius gives larger fragments, which by definition are producedby secondary fragmentation, and a small relative radius gives fine fragments,which by definition are produced by attrition. The relative radius can be relatedto the split factor

=1 2 0 < < 0:50 0:5

(A 73)

XIX

E.3 Estimation of fragmentation rates from large scale experiments

The fragmentation rates can be estimated from experiments in a large scaleboiler. The necessary measurements for this estimation are mass flow andmass distribution of feed fuel and fly char, together with the mass distributionand concentration of fuel particles in the bottom part of the boiler, total mass ofmaterial in the combustor. The mass distribution fuel concentration has only tobe measured in the bottom part of the combustor, since nearly all fuel is locatedin this part. The measured mass distribution in the combustor is assumed tobe representative for the true mass distribution in the combustor. To make areliable estimation of the fragmentation data the accuracy of the measurementshould be evaluated, and a maximum and a minimum mass distribution of thefuel in the combustor had to be determined. The range of the fragmentation datacan then be estimated from the maximum and the minimum mass distributionsof fuel in the combustor.

The estimation of the fragmentation rates during devolatilization and charcombustion and of the relative radius during char combustion can be carriedout as follows:

1. Determine the devolatilization constants, a and b in Eq. A26 and thereaction rate constant, kc during char combustion (literature data).

2. Assume the fragmentation rate function during devolatilization, e.g. Eq.A7-A9.

3. Estimate the minimum and maximum fragmentation rates, kf,dev duringdevolatilization.

4. Estimate the fragmentation rate, kf,char and relative radius, , during charcombustion.

The devolatilization constants and the reaction rate constant for char combustioncan be taken from the literature or can be determined by experiments.Comparison between the calculated mass if no fragmentation occurs and themeasured mass of fuel in the combustor gives an estimation of the accuracyof the chosen reaction rate constant and the devolatilization constants. If themeasured mass is smaller than the calculated one, then the reaction rate and/orthe time for devolatilization are underestimated, because some fragmentationand attrition of the fuel particles takes place in a FBC, and the total mass ofthe fuel will be reduced. This reduction of mass of fuel is most likely largerthan the measurement error. The reaction rate constant, kc, has the greatestinfluence on the total mass of fuel in the combustor and is fuel specific. Dataon the reaction rate constant are available in the literature for different fuels,but the values are scattered and it is difficult to pick the correct reaction rate

XX

constant for the fuel used in a particular experiment. Only a range of possiblevalues can be determined.

The fragmentation rate function, f(R,t) is not known and has therefore to beassumed. Suggestion on assumptions is given by Eq. A7-A9.

The minimum and maximum fragmentation rate, kf,dev, during devolatilization canbe estimated by comparison between calculated and measured mass distributionof fuel in the combustor. Estimation of the minimum fragmentation duringdevolatilization is illustrated in Fig. A10:

1. Assume that no fragmentation occurs and calculate the mass distributionof the fuel during devolatilization, kf,dev=0

2. Compare the mass distribution with the measured one in the combustor3. Increase the fragmentation rate until the calculated mass distribution of the

fuel during devolatilization coincides with the measured mass distribution

[kg/

m]

[m]Particle radius

Mas

s di

stri

butio

n

kf,dev

Figur A 10. Determination of the minimum fragmentation rate. Full line ismeasured mass distribution of fuel in the combustor. The dashedlines are calculated mass distributions of fuel during devolatilizationin the combustor for different fragmentation rates, kf,dev

XXI

The minimum fragmentation rate is then the smallest fragmentation rate, whichfulfils the condition that the mass distribution of the fuel during devolatilizationcoincides with the measured mass distribution. Estimation of the maximumfragmentation rate during devolatilization is illustrated in fig A11:

1. Assume that no fragmentation occurs during char combustion, kf,char=0,and calculate the mass distribution

2. Compare the mass distribution with the measured one in the combustor3. Increase the fragmentation rate, kf,dev until the calculated mass distribution

coincides with the measured mass distribution

The maximum fragmentation rate is then the largest fragmentation rate, whichfulfils the condition that the calculated mass distribution of the fuel, if nofragmentation occurs during the char combustion, and which coincides withthe measured mass distribution.

The fragmentation rate and the relative radius during char combustion areestimated from the measured normalized mass distribution. It can be concludedthat there had been fragmentation during the char combustion, since the numberof char particles leaving with the fly char is much larger than the number ofparticles feed. The particles produced during devolatilization are limited andeven if the largest possible fragmentation rate during devolatilization is used, thenumber of particles after devolatilization is nowhere near the number of particleswhich are leaving with the fly char. Fragmentation during char combustion is thenthe only possible explanation for this dramatic increase of particles of smaller

[kg/

m]

[m]Particle radius

Mas

s di

stri

butio

n

kf,dev

Figur A 11. Determination of the maximum fragmentation rate. Full line ismeasured and dashed lines are calculated mass distributions offuel in the combustor, with different fragmentation rates, kf,dev.

XXII

sizes. The fragmentation rate and the relative radius during char combustioncan be estimated as follow, from Fig. A12:

1. The calculated and the measured normalized mass distributions of the largeparticles are fitted to each other, by changing the value of the fragmentationrate during devolatilization between its minimum and maximum, and thevalue on the fragmentation rate during char combustion. An assumedvalue is used for the relative radius.

2. The relative radius is adjusted so that the small sizes are fitted. Fineradjustment of the fragmentation rates during devolatilization and charcombustion can be necessary.

The fragmentation rates and the relative radius are then taken for the case ofthe best fit between the model and the measured normalized mass distribution.Compare the calculated total mass with the measured one and compare thedata on the fragmentation rates with data from the literature. If the calculatedtotal mass is outside the possible range of the measured total mass in can thisin most cases it can be adjusted by changing the reaction rate constant. Otherparameters which have an influence and have to be investigated in a full analysisis time for devolatilization, fragmentation rate function during devolatilization andprimary distributions of fragments during devolatilization and char combustion.

[1/m

]

[m]Particle radius

Mas

s di

stri

butio

n

kf,char

γchar

Figur A 12. Determination of the fragmentation rates and the relative radius.Full line is measured and dashed lines are calculated normalizedmass distributions of fuel in the combustor, with differentfragmentation rates kf,dev and relative radius

XXIII

Appendix F: Fuel distribution along the riser

In an FBC the bed particles have a rather narrow size distribution, making itpossible to handle the bed particles as a single size. The fuel particles on theother hand, have a wide size distribution, but because the mass of the fuelparticles only corresponds to some percent of the total mass the fuel particlescan be treated as individual particles in a suspension of bed particles. When asingle particle of a different size and density is moving in a suspension it will beaffected by collisions with bed particles. The collision force makes it possiblefor large particles to be transported up through the furnace, even if the dragforce from the gas is not large enough. The collision force is a direct functionof the density of the suspension, where a high density corresponds to a largecollision force and a low density corresponds to a small collision force. Alsothe small particles are affected by this collision force but in an opposite way;the collision force acts in the opposite direction and instead caring the particlesupwards it holds them down. In a CFBC the suspension density is high in thebottom and low in the top. This makes the movement of the fuel particles inthe bottom region controlled by collisions and in the top controlled by the dragforce from the gas. When the movement of the fuel particle is controlled bycollisions, all fuel particles attain approximately the same velocity as the bedparticles. When the movement of the fuel particle is controlled by the drag force,the slip velocity increases with particle size. At a certain particle size the slipvelocity will be larger than the gas velocity, and consequentially the particle willnot be further transported up through the riser. Fig. A13 shows the velocityof the gas up through the furnace, the bed particles, and large and small fuelparticles. The change of suspension density with height in a CFBC makes itnecessary to assume how this influences the vertical distribution of a single fuelparticle size. From knowledge of the action of the collision force on differentparticles sizes the following behavior can be expected: 1. particles with a largerslip velocity than the bed particles have a smaller possibility to be transported upthrough the riser than the bed particles. 2. particles with a smaller slip velocitythan the bed particles have a greater possibility than the bed particles to be

z

ε1

00 zmaxz0

zmax

UGas

Bed particleSmall fuel particle

Large fuel particle

0Figur A 13. Particle and gas velocity versus height in the riser.

XXIV

transported up through the riser. Fig. A14 shows the mass ratio of bed and fuelparticles of different sizes, and also the suspension density. The bed densitydecreases very fast in the riser. For a large particle the density is too low at acertain position to carry the particle any further. But the decrease of the massratio between large fuel particles and bed particles is not immediate, it changessuccessively with the bed density. The small particles experience the opposite,the mass ratio of bed particles and fuel particles increases with decreasing beddensity. The conclusion is that particle velocity and mass ratio of fuel particlesof a given size and bed particles behave in the same way. The fuel and bedparticles can be correlated with each other:

Mfuel(R; z)

Mbed(z)= K

Ufuel(R; z)

Ubed(z)

n

(A 74)

Assuming that the mass ratio is proportional to the possible height, according tothe theory of kinetic energy a particle attain the height:

mgh =mU2

2h =

U2

2g(A 75)

and

Mfuel(R; z)

Mbed(z)= K

hfuel(R; z)

hbed(z)= K

2g

2g

U2

fuel(R; z)

U2

bed(z)= K

Ufuel(R; z)

Ubed(z)

2

(A 76)

The vertical mass distribution of a fuel particle size can then be calculated:

hfuel(R; z) =hbed(z) Ufuel(R; z)=Ubed(z)

2

H

0

hbed(z) Ufuel(R; z)=Ubed(z)2dz

(A 77)

H is the height of the combustor.

z

1

00 zmaxz0

zmax

Small particles

Large particles

0

ρ/ρmax M(R)/Mb

1

Figur A 14. Relative bed density vs. height in the riser and relativemass ratio between fuel particles of a given size and bedparticles related to the ratio in the bottom of the riser.

XXV

Paper III

1

Combustion of wood particles– a particle model for Eulerian calculations

Henrik Thunman, Bo Leckner, Fredrik Niklasson, Filip Johnsson

Department of Energy Conversion,Chalmers University of Technology,S-412 96 Göteborg, Sweden+46 31 7721430, +46 31 7723592 (fax), email [email protected]

(Submitted for publication)

AbstractA simplified thermochemical particle conversion model, independent of particle size andshape, is derived. The model operates with a small number of variables and treats the mostessential features of conversion of solid fuel particles, such as temperature gradients inside theparticle, release of volatiles, shrinkage and swelling, considering also typical shapes (spheres,finite cylinders and parallelepipeds). The model treats the particle in one dimension, and theconversion can be described by the heat and mass transport to the surface of the particle.When modelling a large combustion system this is a great advantage, as the model does nothave to be limited to just a single particle. In fact, it can handle the conversion of a solid phasein a computational cell, where the conversion is related to surface area per unit volumeinstead of surface area of a single particle. The model divides the particle into four layers:moist (virgin) wood, dry wood, char residue and ash. The development of these layers iscomputed as function of time. The model shows satisfactory agreement with measurementsperformed on more than 60 samples of particles of different sizes, wood species and moisturecontents. Comparison with the experiments shows that the simplifications made do notsignificantly influence the overall accuracy of the model. The model also demonstrates thegreat influence of shrinkage on the time of devolatilisation and char combustion.

IntroductionA fuel particle entering a combustor dries and devolatalises. Subsequently, or evensimultaneously if the particle is large enough, the residual char layer is oxidised, and in theend only ash remains. During all these processes the particle shrinks. The conversion of singlesolid fuel particles is usually described by two categories of models. The first concernscombustion in a boiler containing a great number of particles, for example, [1], [2] [3], [4],[5], [6] and [8], where the principal assumption is that a single particle in the combustor canbe treated as thermally thin and that the stages of conversion, drying, devolatilisation and charcombustion, occur in sequence as the temperature of the particle raises. Alternatively, thestages of conversion, starting at the surface of the particle and moving towards the centre, aretreated by an empirical consideration, as a result of heat and mass transport to the surface ofthe particle. The other category of models deals with modelling of the single particle, exposedto a well-defined surrounding. In this type of models the particle is divided into a greatnumber of computational cells, often more than hundred, in order to catch drying,devolatilisation and char combustion while these processes move from the surface to thecentre of the particle, for example, [8], [9], [10], [11], [12] and [13]. Even with this largenumber of cells, the models often only treat one-dimensional particles, such as infinite plates,infinite cylinders and spheres. The weakness of the first category of models is obvious, as thecombustion, especially of large particles, is simplified so much that the combustion behaviourof the particle is missed. The second category of models becomes computationally too heavyand cannot be included in a large computational system describing a large number of particles

2

converted at the same time, for example in a bed of particles, and furthermore, typical particleshapes, such as parallelepipeds and finite cylinders, cannot be treated. There have beenattempts to model different shapes by relating a shape factor, based on the initial particleshape, to heat and mass transfer to the surface of the differently shaped particles, for examplein [14]. However, the conversion phenomena that are to be studied here take place to a largeextent inside the particle, and the particle changes in size during the conversion. Thereforesuch shape factors are not suitable, and a more general formulation of the shape factor isneeded. For this purpose a computationally efficient model should be formulated that operateswith a constant, small number of variables and that is suitable for all particle sizes and shapes.The model should treat essential features of the fuel particle: shape (spheres, finite cylindersand parallelepipeds), temperature gradient inside the particle, shrinkage and swelling of theparticle during conversion. Here, a generalised description of such a particle model will bederived and compared with measurements.

The outline of the discretisation of the particle in such a model is shown for a generalisedparticle in Figure 1. The particle is divided into n layers from the centre to the surface. Thelayers inside the particle are denoted by p, followed by an index that specifies the layer. Here,the particle is divided into four layers: moist (virgin) wood (1), dry, devolatilising fuel (2),char residue (3) and ash (4). The boundaries between these layers are denoted by b followedby an index specifying the stage of combustion related to the boundary: drying (1),devolatilisation (2), char combustion (3) and particle surface (4). The amount of fuel at acertain stage of combustion inside a particle determines the size of the layer. As theconversion of the fuel particle proceeds, solid matter will leave layer j and enter layer j+1.The drying, devolatilisation and char combustion fronts moving from the surface to the centreof the particle coincide with the boundaries between the layers.

In order to validate the model, more than 60 wood samples were dried and devolatalised in aninert atmosphere, followed by burnout of the remaining char in a nitrogen-oxygenatmosphere.

b,4

p,4

b,3

p,3

b,2

p,2

b,1

p,1

Figure 1. Fuel particle consisting of p,1..4 solid layers and b,1..4 boundaries between thelayers. The dashed line indicates the initial shape of the particle before shrinkage.

3

Theory

In a generalised particle, such as in Figure 1, all heat and gas produced pass a control surface,whose position depends on the radius r, as expressed in the conservation equations. Thiscontrol surface Γ is related to a control volume V as

dr dVΓ = (1)

Applied to a spherical volume the control surface, that is, the shape factor, becomes Γ=4πr2,and for the well-known cases of infinite cylinder and infinite plate the shape factor Γ is 2πrand 1, respectively. The shape factor can be derived for a finite fuel particle of any shape,implicitly assuming an isotropic behaviour of the particle or that representative mean valuesover the surface Γ can be formulated. The derivation based on Eq (1) assumes that theposition of the control surface is determined by the requirement of equal distance from thesurface of the particle. Hence, for a finite cylinder of initial length l and initial diameter d weobtain

( )( )22 3r r l dπΓ = + − (2)

and for a parallelepiped with the initial dimensions l1 × l2 × l3, where l1 represents the shortestend

( ) ( )( ) ( ) ( )22 1 3 1 2 1 3 124 8 2r r l l l l l l l lΓ = + − + − + − − (3)

With this definition the starting location of the radius (r0), which for a sphere is r0 =0,becomes a line for a long cylinder (l>d) or a plate for a short cylinder (l<d) and aparallelepiped. This is illustrated for a finite cylinder in Figure 2. For all shapes, the startinglocation of the radius is r0 =0, except for a short cylinder, where the starting location isr0=(d-l)/2. In the one-dimensional model the effects of anisotropic material and corners (finitecylinders and parallelepipeds) are averaged over the surface Γ, and therefore it is important toalso give physical and thermo-chemical data in the form of surface averaged values.

d/2d/2

r0=0

l

dr0=(d-l)/2l/2

l/2

r

r

l

l

d

dr

r

l

d

Figure 2. Definition of the starting position of the radius r0 and the control surface Γ (solid) atradius r inside a finite cylinder (dashed) having a length l, longer or shorter than thediameter d.

4

In [15] a one-dimensional model is presented for simultaneous drying and devolatilisation of asingle particle having the shape of a sphere, an infinite cylinder or an infinite plate. Thismodel is expanded here to include char combustion, shrinkage and the two particle shapestreated above, finite cylinder and parallelepiped. The model [15] was derived under theassumptions of thermal equilibrium between gas and solid phases inside the particle, no gasphase reactions inside the particle, immediate release to the surrounding of gases produced,homogeneous heating of the particle’s surface, and evaporation of water in an infinitelynarrow region inside the fuel particle. By adding the assumption that also devolatilisation andchar combustion take place in infinitly narrow regions inside the particle (covered by the ashlayer), the conversion of the single particle can be described by the following energyconservation equation in one dimension,

( ) ( ),4 *, , ,

,

1 1p p bp p p b j b j s j

j b j

I TB T k r r R i

t r r rδ

′′′∂ ∂ Γ ∂ ∂ ′′+ Γ = Γ + − ∂ Γ ∂ Γ ∂ ∂ Γ ∑ (4)

Here I is enthalpy, B is heat capacity flow per unit area, T temperature, R reaction rate, δ deltafunction, i specific enthalpy and index s indicates a component in the solid. The heat capacityflow per unit area, originating from the conversion of the solid fuel to gas, is given by

( )0

*, , *

,4 , ,

rb j b j

p b i j g ij ir

r r RB dr X c

δ ′′− = Γ Γ

∑ ∑∫ (5)

where c is specific heat and X is molar stoichiometric coefficient for species i in reaction j.

The continuous formulation of conversion of a particle, Eq (4), is discretisized into four layersby averaging temperature, physical and thermo-chemical data across each layer. Theboundaries of the layers inside the particle coincide with the combustion stages and are giventhe same index (b) as shown in Figure 1. The source terms are now placed in the boundariesbetween the layers, as seen in Figure 3. By doing so, the source terms can be removed fromthe energy equation (Eq. (4)) for the single layer. Instead they will appear in the boundaryconditions, and an additional convective flow is introduced (the third term in Eq. (6)) to

q q j+1

b,j

A) B)

j

Figure 3. Section of fuel particle. Centre line dashed-dotted. A) A heat source/sink, q, locatedin a layer, according to Eq. (4). B) Same as A) but with the heat source/sink located at theboundary b,j. When the boundary moves during conversion of the particle, as indicated by anarrow, mass leaves layer j for layer j+1.

5

represent the solids that leave layer j for layer j+1 when the boundaries move toward thecentre of the particle. The energy conservation equation of a single layer j then becomes,

( ) ( )

,

, 1

1

,4 , , ,1

,

,

4 4

0, 0,

,4 , 1 , , 1 , , ,0, 1 0,

,

,, , , , 1 ,

, , 1

2

b j

b j

Tj

b b k k i g ik i Tp j

p j

k kk j k j

b b j p j b j b j p j b jj j

p j

p jb j b j p j b j p

b j b j

R X c dTI

t V

R i T R i T

V

kT T T

r r

ξ ξ

ξ ξ

−

−

=

= =− −

−

−−

′′ Γ ′′′∂ + −

∂

Σ Σ ′′ ′′Γ − − =

Γ − −Γ−

∑ ∑ ∫

( )( ), 1

,

j b j

p j

T

V

−−

(6)

Tp,j is the mean temperature of layer j, assumed to be equal to the temperature at the centre ofthe layer at, (rb,j+rb,j−1)/2. The amount of the components is expressed by a mean molarfraction in the particle, ξ, related to the molar concentration C0, of the virgin fuel,

( )0

/ 1m m v c ad

m v c a

Y Y Y Y YC

M M M Mρ

− = + + +

(7)

where ρ is density, Y mass fraction related to initial fuel properties, and M is molar mass. Themass fraction of moisture Y1 related to dry solid, is equal to Ym/(1-Ym). The initial mean molarfraction of components i in the fuel is

0,0

/d i ii

Y M

C

ρξ = (8)

where subscript i is 1 (moisture), 2 (volatiles), 3 (char) and 4 (ash). The specific enthalpy ofsolids in a layer at a given temperature inside the particle results from the specific enthalpiesof the remaining solid components and the initial mean molar fractions in the layer as,

4 4

, 0, , 0,p j k s k kk j k j

i i Tξ ξ= =

= ∑ ∑ (9)

The volume of a single layer j is obtained from the definition of the shape factor, Eq (1).

,

, 1

,

b j

b j

r

p j

r

V dr−

= Γ∫ (10)

Eq. (6) is simplified by using enthalpy of each layer instead of enthalpy per unit volume andby expressing the integration over the heat capacity with an enthalpy difference,

6

( )

( ) ( ) ( )( )

1,

,4 , , , , , , 11

4 4

0, 0,

,4 , 1 , , 1 , , ,0, 1 0,

,, , , , 1 , , 1

, , 1

2

jp j

b b k k i g i b j g i b jk i

k kk j k j

b b j p j b j b j p j b jj j

p jb j b j p j b j p j b j

b j b j

IR X i T i T

t

R i T R i T

kT T T T

r r

ξ ξ

ξ ξ

−

−=

= =− −

−

− −−

∂ ′′+ Γ − − ∂ Σ Σ ′′ ′′− Γ − =

Γ − −Γ −−

∑ ∑

(11)

In Eq. (11) the shrinkage of the particle can be easily handled, as only position and area of theboundaries have to be calculated. This is done by means of the volume of each particle layer,which is given by the initial volume of the particle, Vp0, the volume ratio of a layer inside theparticle, Λp,j, and an empirical shrinkage factor of the particle layer, θp,j.

, 0 , ,p j p p j p jV V θ= Λ (12)

The initial volume is defined as,

0,4

0

0

br

p

r

V dr= Γ∫ (13)

The volume ratio of a layer inside the particle, Λp,j, is related to a non-shrinking particle and isexpressed by the present and initial molar fractions of the compounds in the solid phase,

1,

0, 0, 1

j jp j

j j

ξ ξξ ξ

−

−

Λ = −

(14)

The empirical shrinkage factor of the volume element is defined as the ratio of the volume atcombustion stage j to the initial volume.

The mean temperature in a layer is given by the enthalpy of the layer,

4

, 0 , 0 0, , ,p j p p j s k p j p jk j

I V C i Tξ=

= Λ ∑ (15)

Initially the particle consists of moist virgin wood, whose enthalpy is,

0,1 0 0 ,1p p s pI V C i= (16)

0,2 0,3 0,4 0p p pI I I= = = (17)

For calculation purposes the layers need to have some extension in space, and therefore theminimum volume of a layer is restricted to a volume corresponding to ξi/ξ0,i=10-4.The boundary conditions of the entire particle are:At the calculation centre (r = r0)

7

0T

r

∂ =∂

(18)

and at the surface of the particle (r = rb,4)

,4p rad conv cond

Tk q q q

r

∂ ′′ ′′ ′′− = + +∂

(19)

Subscript conv indicates external convection and cond external conduction. The radiative heattransfer to the surface of the particle is,

( )4 4,4rad rad bq T Tε σ ∞′′ = − (20)

In the present calculation convective and conductive heat transfer to the surface of the particleare treated together, estimated by a single heat transfer coefficient, h,

( ),4conv cond bq q h T T∞′′ ′′+ = − (21)

The boundary conditions for the individual layers inside the particle, which give thetemperatures at the boundaries, are:At the calculation centre (r = r0),

,0 ,1b pT T= (22)

At the drying boundary (r = rb,1),

( ) ( ),2 ,1,2 ,1 ,1 ,1 ,1

,2 ,1 ,1 ,

2 2p p mp b b p b

b b b s m

k k HT T T T R

r r r M′′− − − =

−(23)

At the devolatilisation boundary (r = rb,2),

( ) ( ),3 ,2,3 ,2 ,2 ,2 ,2

,3 ,2 ,2 ,1 ,

2 2p p vp b b p b

b b b b s v

k k HT T T T R

r r r r M′′− − − =

− −(24)

At the char combustion boundary (r = rb,3),

( ) ( ),4 ,3,4 ,3 ,3 ,3 ,3

,4 ,3 ,3 ,2

2 2p p cp b b p b

b b b b C

k k HT T T T R

r r r r M′′− − − =

− −(25)

At the surface of the particle (r = rb,4),

( ) ( )2 2 2

,4 * *1,4 ,4 ,4 , , ,2

,4 ,3

2 prad conv cond b p b g H g O g H O

b b

kq q q T T R i i i

r r′′ ′′ ′′ ′′+ + − − = + −

−(26)

8

The ash layer is assumed to be inert and fixed on the surface of the particle during the entireconversion process. Despite this assumption there is a reaction rate given in Eq (26). This isthe rate of combustion of the volatile gases flowing out, which meet the oxygen transportedby diffusion from the bulk gas to the surface of the particle. In the model, the combustion ofthe volatile gases flowing out is limited to combustion of hydrogen. This formulation of thesurface temperature, Tb,4, causes a severe instability in numerical computations, sinceconvection, conduction and especially radiation are very sensitive to the surface temperature.Also heat generation at the boundary of the char layer can cause a stability problem if there isa rapid change in the oxygen concentration. To overcome these problems, the surfacetemperature is assumed to be equal to the temperature of the ash layer (Tb,4=Tp,4) and the heatsources at the char and ash boundaries are placed inside the ash layer. By doing so, the charboundary condition, Eq (25), becomes,

( ) ( ),4 ,3,4 ,3 ,3 ,3

,4 ,3 ,3 ,2

2 20p p

p b b pp p p p

k kT T T T

r r r r− − − =

− −(27)

and the ash boundary condition, Eq. (26), disappears. Instead, a source term, qp,4, is added toEq (11) to represent the ash layer. This source term includes the source terms at theboundaries of the char and ash layers,

( )2 2 2

*1,4 ,4 ,4 , , , ,3 ,32

cp rad conv cond p p g H g O g H O p p

C

Hq q q q R i i i R

M′′ ′′ ′′ ′′ ′′= + + −Γ + − −Γ (28)

Phase change reactionsThe phase change reactions are related to vaporization of water, devolatilisation of volatilesand gasification of char. The vaporisation of water at low heating rates is caused by acombination of heat and mass transfer inside the particle. If the heating rate is high, thevaporisation mostly depends on internal heat transfer and the influence of the mass transfer onvaporisation is neglected. At ambient pressure, the saturation temperature for vaporisation is100°C, but inside the particle it becomes somewhat higher due to the pressure increase causedby the volume expansion during gasification of water. No re-condensation of water isconsidered in the model. The temperature gradient in the particle is steep, and the exacttemperature of vaporisation is of little interest. Therefore it is sufficient to know that the wateris vaporised close to the saturation temperature. This can be expressed by modelling the rateof vaporisation by an Arrhenius expression with a steep gradient around the saturationtemperature. Hence, a rate of vaporisation at ambient pressure has been derived for theseconditions

[ ]0 0 ,1 271,1 0 1

,4 ,4

10 exp 25000 /p bb s

b b

C VR C T

t

ξ ξ − Γ∂ ′′ = − = Γ ∂ Γ

(29)

The rate of devolatilisation is expressed by three competing reactions in a one-stepmechanism according to [9],

9

[ ]0,2

0

81 1

82 2

73 3

30 0 00 22

,21,4 ,4

1.3 10 16875

2 10 16009

1.1 10 14602

expbr

pb i i

ib b r

E

A E

A E

A E

C V CR A T dr

t

ξξ=

−

= ⋅ == ⋅ == ⋅ =

∂ ′′ = − = Γ ∂ Γ Γ∑∫

(30)

where superscript 0 indicate coordinates for the case of no shrinking. There are a greatnumber of other reaction mechanisms for devolatilisation of wood, given for example in [10],[16], [17], [18]. The choice of the reaction mechanism in [9] is made only to get a reactionrate that releases volatiles at approximately the right temperature level, and if the char yield,(1-Yv), is not known, this reaction mechanism gives approximately the correct level of thechar yield, given by the last term in the mechanism multiplied by 0.9. The char yieldcalculated from [9] is obtained from an iterative solution of

[ ]( )

0,2

0

03 3 00.9 exp /

1 ;

br

pr

v a

A E T dr Vt

Y Y t

χ

χ

⋅ −∂ = Γ∂− = + →∞

∫ (31)

where χ is the mass fraction of the combustible part of the fuel, related to its initial mass.Devolatilisation is a thermal decomposition of the fuel, and volatiles are released in the entireregion between the centre of the particle and the char layer, but due to the steep temperaturegradient inside the particle most of the volatiles are released close to the char layer where thetemperature is highest. This justifies the assumption that the volatiles are released in a frontthat moves from the surface to the centre of the particle. To compensate for the volatiles thatare released before the arrival of the devolatilisation front, the reaction rate in Eq (30) and(31), is expressed as the rate of devolatilisation integrated from the centre of the particle (r0)to the boundary of the dry fuel layer (rb,2), and divided by the boundary area of this layer.Between the centre of the particle and the boundary of the dry layer, the temperature isassumed to be piecewise linear from the mean temperature of the wet (virgin) layer to theboundary of the wet layer, (rb,1), to the mean temperature of the dry layer and to the boundaryof the dry layer. The gases produced during devolatilisation of biofuel consist of CO, CO2,H2O, H2, light hydrocarbons and of small quantities of heavy organic compounds. Thecomposition of the volatile gases can be determined as a result of energy and speciesbalances, [19].

The reactions at the char boundary are modelled as a sum of four reactions

( ) ( )c 2 c c 2

2

2 2

2 4

Ω C+O 2 Ω -1 CO+ 2-Ω CO

C+CO 2CO

C+H O CO+H

C+2H CH

I

II

III

IV

⇒

⇒⇒⇒

whose rate is

10

( )0 0 ,33,3 , , , ,

,4 ,4

p bb b I b II b III b IV

b b

C VR R R R R

t

ξ Γ∂ ′′ ′′ ′′ ′′ ′′= − = + + + Γ ∂ Γ (32)

Char from wood produced under rapid devolatilisation always contains small fractions ofoxygen and hydrogen as illustrated by the fuel used in the present experiments, see Table 1.For simplicity the fractions of oxygen and hydrogen are not included in the reaction schemerepresented by reactions I to IV. The char is predominantly gasified by a reaction betweenchar and oxygen (reaction I),

( ) ( )( )2

11 1, ,1b I c O r I dR Cα ηβ β

−− −′′ = − Ω + (33)

where α is the fraction of oxygen consumed by volatile gases to be explained below. If theoxygen is consumed, the char can be gasified by carbon dioxide, water vapour and/orhydrogen (reaction II, III, IV),

( )( ) 11 1, ,b i i r i dR C ηβ β

−− −′′ = + (34)

where i represents the reaction. The rates of gasification, Eq. (33) and (34), are functions ofthe rate of the diffusion of the reactant from the bulk into the reactive surface, βd, and thereaction rate, at the reactive surface, βr, compensated by an efficiency factor, η,

3 0,3

3 0,3

/

/ c

ξ ξη

ξ ξ ψ=

+(35)

The efficiency factor takes into account the extension of the reaction front, ψc in the particle.In the model ψc is assumed to be 0.01. The oxidation rate of char by oxygen is [20],

[ ], 1.715 exp 9000 /r I T Tβ −= (36)

A correlation for the formation of carbon monoxide and carbon dioxide, Ωc, is given by thefollowing expression [20] obtained in conjunction with Eq (36),

[ ]( )[ ]

2 1 4.3exp 3390 /

2 4.3exp 3390 /c

T

T

−

−

+Ω =

+(37)

The reaction rate chosen for charcoal from biomass, Eq (33) is similar to reaction rates usedfor biomass char in Russian literature, [21]. Gasification rates for water vapour, carbondioxide and hydrogen are those of lignite, [3],

[ ]3, , ,10 3.42 exp 15600 /r II r III r IV T Tβ β β −= = = (38)

Even if char from lignite is not a charcoal from wood, the reaction rate is close to that ofcharcoal, as seen from a comparison between the oxidation rate of charcoal from biomass [20]and char from lignite [3]. There are other reaction rates of the gasification reactions available

11

in the literature, for example in, [22] and [23]. In [23] other proposed rates are validated, bycomparing model calculations of single particles with measurements, but the resultingreaction rates are complex, and since the gasification process is of secondary interest here,they are not included.

The assumption made here, that also the char conversion takes place in an infinitely narrowregion, can be motivated by the high heating rate of the particle during combustion, whichcreates a steep temperature gradient inside the particle, and also by the fact that theconversion of char is controlled by diffusion of oxygen from the bulk to the surface of theparticle. The conversion of char is controlled by external diffusion in nearly all combustionsituations in fixed or fluidised beds, where the char is converted by oxygen. On the otherhand, modelling of gasification as taking place on reaction surfaces is a great simplification.For some gasification situations the reaction rate totally controls the conversion of the char,and the intrinsic surface area of the fuel particle becomes of most interest. Hence, with thereaction rate expressions selected in the present formulation the model is mainly intended forsituations when char is converted by fast oxidation reactions. The consideration that diffusionof the oxidant from the bulk is the rate-determining step of char combustion is also asimplification during simultaneous devolatilisation and vaporisation. Then there is an outflowfrom the interior of the particle of the oxidants water vapour, carbon dioxide and hydrogen,which are assumed not to gasify the char on its way out of the particle. Furthermore, theoxygen that is transported to the surface of the particle by diffusion not only oxidises the charbut also the volatiles, flowing out from the interior of the particle. This is taken into accountonly for hydrogen, which has a much higher reaction rate than char. The hydrogen flowingout as a part of the volatiles is assumed to consume the oxygen before the char, at the ashboundary

2,4 2b O dR Cα β′′ = (39)

The fraction of the oxygen that is consumed by the hydrogen is α,

2

2

,2 2, 1 1,21

1,4

; 1;

1 ; 12b Hs

s O d

R X

C

α αα α

αβ′′ ≤Γ

= = >Γ (40)

Table 1. Properties of fuel used in the measurements

Birch/Char Spruce/CharAsh (% mass, dry) 0.3/2.0(a) 0.4/2.0(a)

Density (kg/m3) 540±40/- 420±40/-H (MJ/kg) 18.4/33.6(b) 18.8/33.2(b)

ElementalAnalysis(c)

C 49.2/93.6 50.2/92.6O (by difference) 44.3/5.1 43.5/6.4H 6.3/0.7 6.3/0.8N 0.16/0.45 0.10/0.23S <0.01/ - <0.01/ -(a) calculated, (b) ash free, (c) % mass, dry ash free fuel

12

MeasurementsIn order to validate the model, experiments were carried out in a laboratory fluidised bedreactor. In this reactor more than 60 wood particles, having sizes as used in utility boilers,were dried and pyrolysed in an inert atmosphere, followed by burnout of the remaining char.The composition of gas components was continuously measured. To a large extent the fuelparticles were floating on the surface of the fluidised bed during the thermochemicalconversion. Especially larger birch particles fell apart at the end of the devolatilisation phase.The Biot number was above 6 for all particle sizes. Hence, internal heat transfer controls theheating of the particles and the choice of reactor for the experiments does not affect theresults.

The fuel particles were prepared from raw wood of birch (hardwood) and of spruce(softwood), with material properties as shown in Table 1. Parallelepipeds of eight sizes weretested. The particles were cut with the long side (varied between 10 and 40 mm) along thefibre direction of the wood and with the shortest end (varied between 3 and 10 mm) always inthe perpendicular direction. The sizes were chosen to cover the range of specific areas(surface-area to volume ratios), 320-800 m-1, that is expected to occur in a batch of forestwaste wood as fired in utility boilers. Each wood-particle size was tested for birch and forspruce, as received (birch, 35 to 45% and spruce, 60 to 65% moisture) and after drying for 24hours in an oven at 377 K. To simplify the validation of the different combustion stages,drying, devolatilisation and burnout of char, the particles were pyrolysed in an inertatmosphere, followed by burnout of the remaining char in air. Further details on theexperimental conditions and set-up are reported in [19].

Table 2. Physical properties, S is initial specific area, Γb,4/Vp0

= a1+a2TPropertya1 a2

k [W/mK] ^ / || 0.52 / 0.73 -

kw [W/mK] 0.278 1.11⋅10-3

kc [W/mK] 1.47 1.1⋅10-3

ρsd [kg/m3] 1480 -

ρw [kg/m3] 1000 -

ρc [kg/m3] 1950 -

Dg [m2/s] = a1T ^a2 2.03⋅10-10 2

= a1+a2SPropertya1 a2 (×10-3)

Y3+Y4 [-]spruce/birch

0.245/0.194 -0.094/-0.092

13

Physical data used in the model

The mass and heat transfer coefficients are estimated Appendix A [24], and the mass transfercoefficient is compensated for the out-flowing gases [25]. The thermal conductivity, kp,i, is anaveraged value over the surface Γ, where the effective conductivity for a surface element isgiven perpendicular or parallel to the fibre direction. The thermal conductivities of wood andchar are estimated according to Appendix B, [26]. The diffusivity in the gas mixture is givenin Table 2, by assuming a binary gas consisting of CO2-O2 at ambient pressure, [27]. Thespecific enthalpies at reference temperature and the temperature dependent specific heat forgas and solid species are taken from [19], according to which the composition of the volatilegases is calculated. For simplicity, since the ash content is small, the ash is assumed to havethe same specific enthalpy and conductivity as the solid part of the char.

Comparison between model and measurement

Measured and calculated devolatilisation times are compared in Figure 4. The devolatilisationtime, more or less starting from the time of introduction of the fuel particle into the reactor, isdefined to last until 95% of the volatiles are released. The model predicts the time ofdevolatilisation within 20%, with an overestimation, especially for the larger particle sizes.There are mainly two reasons for the discrepancy: larger particles form cracks or fall apartduring devolatilisation which enhances the area for heat transfer from the surrounding andlowers the thermal distance inside the particle; the second reason is the discretisation of theparticle in only four layers. The overestimation caused by the discretisation increases withparticle size and decreases with a growing difference between the surrounding temperatureand the temperature of devolatilisation. The error is small in the outermost position and thengrows with the distance from the surface of the particle. This is a result of the assumption of alinear temperature distribution inside the layer, and the theoretical error is largest for sphericalparticles. However, most of the mass of a spherical particle is located in the outer part of theparticle, and this makes the error small for release of mass, but it may be non-negligible fortime of mass release. For parallelepipeds and finite cylinders this effect to some extent iscompensated for by the shape factor, which causes an underestimation, because the cornereffect of the heat transport into the interior of the particle is not exactly represented.

0 100 2000

50

100

150

200

Calculated time [s]

Mea

sure

d tim

e [s

]

-20%

20%

0 200 4000

100

200

300

400

Calculated time [s]

Mea

sure

d tim

e [s

]

20%

-20%

Figure 4. Comparison between calculated Figure 5. Comparison between calculatedand measured time of devolatilisation for 61 and measured time of char combustion for

samples of, wet (o) and dry ( ) spruce, and 61 samples of, wet (o) and dry ( ) spruce,

wet (∗) and dry (+) birch. and wet (∗) and dry (+) birch.

14

0 200 4000

200

400

Calculated time [s]

Mea

sure

d tim

e [s

]

300 500 700 900 1100

0 200 400 6000

1

2

3

4

5x 10

-3

Time [s]

Par

ticle

radi

us [m

]

T[K]

21

3 4

Figure 6. Times of devolatilisation (o) and Figure 7. Example of simulated temperaturechar combustion (∗). Arrows indicate the and positions of drying (1), devolatilisation (2),influence of increasing shrinkage. char combustion (3) and particle surface (4)

inside a wet spruce particle as a function oftime.

The largest underestimation caused by the shape factor is for cubic particles and cylinders,having the same length as diameter. As the particle shape approaches an infinite plate orinfinite cylinder the error disappears. It is difficult to quantify this error, since it stronglydepends on size, particle shape, heating rate and final temperature, but the influence of thediscrepancy on the result is not great for the most common particle sizes used in boilers asseen in Figure 4. However, the model is not suitable for very large particles, for examplewood logs, devolatalised at low temperature (less than 873K).

Figure 5 compares measured and calculated times of final char burnout, defined as the timebetween the introduction of air into the reactor, or in the calculation, and 95% burnout. Herethe scatter is much larger than for devolatilisation, but the agreement is still good. One of themain reasons for the larger scatter during char burnout than during devolatilisation is theaccuracy of the correlation for char yield (Table 2), which is plus minus 10%. Other reasonsare that some fuel particles fall apart in the end of devolatilisation, especially large birchparticles, and finally, the accuracy of the mass transfer coefficient is plus minus 20%. Themass transfer coefficients are related to spheres, and other shapes are accounted for by anequivalent diameter based on the surface area of the particle. This may have some limitations,and can be the reason for the large scatter for the thinnest particles, which thermally more orless can be represented as infinite plates.

The only parameter that has a great effect on the conversion, but cannot be satisfactorymeasured, is the shrinkage of the particles. Although the shrinkage is difficult to measure,attempts were made to do so. The difficulties in measurement of shrinkage during drying are,for example, that the particles were exposed to a much lower final temperature and heatingrate than particles in the experiments, in order to separate drying from devolatilisation.Furthermore, measurement of shrinkage during devolatilisation becomes complicated, sincethe char particles produced are fragile and large cracks are formed inside the particles.Especially large birch particles may fall apart. The measured shrinkage during drying for bothwood species was between 10 and 15%. During devolatilisation the measured shrinkage,related to a dry particle, was between 35 and 50% for birch, and for spruce more than 20%. Inthe calculation the shrinkage was assigned to 10% during drying, and to 39%, (θ2=0.55), forbirch, 28% (θ2=0.65) for dry spruce, and 39% for wet spruce during devolatilisation. Dry and

15

wet spruce is given different shrinkages, because the time of char combustion is shorter forinitially dry particles than for initially wet particles of the same size. Since char combustion iscontrolled by diffusion of oxygen from the bulk of the surrounding gas to the surface of theparticle, the only variable that can cause this difference is a smaller surface area of theparticles. The conclusion is that wet particles shrink more than dry particles. In Figure 6 timesof devolatilisation and char combustion are calculated for three wet spruce particles of thesize of 10×25×40mm. The shrinkage was assumed to be 10% during drying and 6, 28 and39% (θ2=0.85, 0.65 and 0.55) during devolatilisation. The figure shows that the time ofdevolatilisation decreases with increasing shrinkage, because the remaining wood becomescompact, and this results in a higher thermal conductivity and consequently in an increasedheat transport inside the particle. In contrast, the time of char burnout increases with increasedshrinkage as a result of smaller surface area.

0 100 200 300 400 5000

0.25

0.5

0.75

1x 10

-4

Sim

ulat

ed [k

g/s]

0 100 200 300 400 5000

0.25

0.5

0.75

1

Time [s]

0 100 200 300 400 5000

0.25

0.5

0.75

1x 10

-4

Sim

ulat

ed [k

g/s]

0 100 200 300 400 5000

0.25

0.5

0.75

1

Time [s]

400 500 600 700 8000

2

4

6

8x 10

-6

Sim

ulat

ed [k

g/s]

400 500 600 700 8000

0.25

0.5

0.75

1

Time [s]

Mea

sure

d (N

orna

lised

)M

easu

red

(Nor

nalis

ed)

Mea

sure

d (N

orna

lised

)

x 10-1

a.

b.

c.

0 100 200 300 400 5000

0.25

0.5

0.75

1x 10

-4

Sim

ulat

ed [k

g/s]

0 100 200 300 400 5000

0.25

0.5

0.75

1

Time [s]

0 100 200 300 400 5000

0.25

0.5

0.75

1x 10

-4

Sim

ulat

ed [k

g/s]

0 100 200 300 400 5000

0.25

0.5

0.75

1

Time [s]

400 500 600 700 8000

2

4

6

8

x 10

-6

Sim

ulat

ed [k

g/s]

400 500 600 700 8000

0.25

0.5

0.75

1

Time [s]

Mea

sure

d (N

orna

lised

)M

easu

red

(Nor

nalis

ed)

Mea

sure

d (N

orna

lised

)

x 10-1

a.

b.

c.

Figure 8. Measured normalised (solid line) Figure 9. Measured normalised (solid line)and simulated (dashed line) mass release and simulated (dashed line) mass release ofof water, (water in volatiles + moisture, a.), water, (water in volatiles + moisture, a.),volatiles (b.) and char (c) as a function of volatiles (b.) and char (c) as a function of timetime for a spruce particle of the size of for a birch particle of the size of 10×25×40 mm,10×25×40 mm, with a moisture content with a moisture content of around 40%.of around 60%.

16

Figure 7 shows a simulation of a 10×25×40 mm moist spruce particle: temperatures andwidths of the four layers change with time, as the reaction fronts move from the surface to thecentre of the particle. Figures 8 and 9 give representative examples of comparisons betweenmeasurements and simulations for spruce (Figure 8) with a moisture content around 60% andfor birch (Figure 9) with a moisture content of around 40%, both of the size of 10×25×40 mm.The measured and simulated release of water, volatiles and burnout of char are shown. Themeasured concentration of water originates from the moisture in the fuel and to a small extentfrom the volatile gases. The volatiles are assumed to have a constant composition during thewhole devolatilisation, and the measured rate of the devolatilisation is related to the measuredCO concentration. The char is predominantly converted to CO2, and the measured release ofchar is related to the measured CO2 concentration. The releases of water, volatiles and charare observed as gas concentrations, and are not directly measured as mass release. Forcomparison with the simulated releases, they are therefore normalised to the highest measuredconcentration of water. However, this value is not exactly represented by the simulation,which results in an almost instantaneous peak of water (Figure 8a, 9a) as the particle entersthe reactor, followed by a peak of volatiles (Figure 8b, 9b). The instantaneous peak of water,released from the surface of the particle, was correctly obtained by the simulation (asconfirmed by visual observations during measurements), but could not be captured by the gasanalyser (the FTIR) because its response time was not sufficiently short. For a fair comparisononly the main part of the simulated water release is shown in Figure 8a and 9a. After theinitial peaks, water and volatiles decline until all moisture is released. Then, the temperaturein the centre of the particle rises rapidly, because the heat sink caused by evaporationdisappears. This results in a second peak of water and volatiles, as a consequence ofenhancement of devolatilisation. After the second peak the levels of water and volatilesdecline once more until the devolatilisation is finished. The trends in release of water andvolatiles of both spruce and birch particles are reasonably well described by the model.However, in the case of spruce, the second peak of the measured volatile release is moreextended in time than that obtained from the simulations, probably a result of cracks formedin the particle. For the birch the agreement is very good.

After 350 seconds air is turned on and the final burnout of the char starts (as seen in Figures8c, 9c). As the char burns out, the surface rate of the char conversion decreases nearly linearlyuntil complete char burnout, because the reaction surface diminishes when the combustionfront approaches the centre of the particle, which can be seen both from measurements andsimulations. As already stated above, agreement between measured and simulated times forchar burnout is not as good as the predicted times of devolatilisation, as seen from Figure 8and 9. The measured time of burnout of spruce is much longer than simulated, whereas it isshorter for birch. The much shorter time for the birch, as already mentioned, results from thedisintegration of the birch particles. For spruce there is an almost perfect agreement betweenmeasured and simulated time for the nearly linear decrease in char combustion. Thesimulations show a sudden end of the char burnout, whereas measured char burnout endsslowly. This is probably a result of tree-dimensional effects, which cannot be properlymodelled with the one-dimensional model.

ConclusionsA simplified thermochemical particle conversion model is derived, for use in a comprehensivemodel of a fuel bed. The model is independent of size and shape of the particle and operateswith a low number of variables. It includes the most essential features of conversion of a solidfuel particle, such as fuel shapes (spheres, finite cylinders and parallelepipeds), temperature

17

gradient inside the particles, shrinkage and swelling. The model treats the particle in onedimension independent of shape, and the conversion of the particle can be described by theheat and mass transport to the surface of the particle. When modelling a large combustionsystem this is a great advantage, since it extends the validity of the model beyond thetreatment of just a single particle. In fact, it can handle the conversion of a solid phase in acomputational cell, where the conversion is related to surface area per unit volume instead ofsurface area of a single particle.

The model is validated numerically by a heat and mass balance, and it agrees well withmeasurements performed on more than 60 samples of particles of different sizes, woodspecies and moisture contents. A comparison with the experiments shows that thesimplifications made do not significantly influence the overall agreement of the model. Themodel calculations predict the great influence from shrinkage on time of devolatilisation andchar combustion in agreement with experiments. Larger shrinkage results in a more compactchar layer, and consequently higher thermal conductivity and a shorter time fordevolatilisation. On the other hand, for char combustion the trends are the opposite: increasedshrinkage means a smaller external surface, as shown by the model.

AcknowledgmentThe project was financed by grant from the Swedish National Energy Board

NomenclatureA [1/s] Pre-exponential factorAr [ - ] Archimedes number Ar = gd3(ρs-ρg)/( νg

2ρg )B [W/m2K] Heat capacity flow per unit areaC [mole/m3] Molar concentration, related respective phaseD [m2/s] Molecular diffusion, or particle dispersionE [K] Activation energy divided by gas constantH [J/kg] Lower heating valueI [J] EnthalpyM [kg/mole] Molar massN [mole] MoleP [Pa] PressurePr [ - ] Prandtl number Pr = νgcgρg/kg

R [mole/s] Global reaction rateRe [ - ] Reynolds number Re = ugdeq/νg

S [m2/m3] Specific area, Γb,4/Vp0

Sc [ - ] Schmidt number Sc = νg/Dg

T [K] TemperatureV [m3] VolumeX [ - ] Molar stoichiometric coefficient for species i in reaction jY [ - ] Mass fraction, related to dry fuel propertiesb [ - ] Reduction factor, compensating for gas outflowc [J/kgK] Specific heatd [m] Particle diameterh [W/m2K] Heat transfer coefficient gas-particlei [J/mole] Specific enthalpyk [W/mK] Heat conductivityl [m] Initial length of particles

18

q [W/m2] Heat flowr [m] Particle radiust [s] Timeu [m/s] Local velocityGreekΓ [m2] Shape factor, equal to area at particle radius rΛ [ - ] Volume fractionΩ [ - ] Stoichiometric ratio or molar fraction between two speciesα [ - ] Fraction of oxygen consumed by volatile gases inside particleβ [m/s] Mass transfer coefficient, or reaction rateχ [ - ] Mass fraction of the combustible part in the fuel, related to its initial massδ [1/m] Delta functionεmf [ - ] Bed voidage at minimum fluidisationεrad [ - ] Emissivityη [ - ] Efficiency factorν [m2/s] Kinematic viscosityθ [ - ] Shrinkage coefficient, volume of a finite volume related to its initial

volumeρ [kg/m3] Densityσ [W/m2K4] Stefan-Boltzmann constant, 5.67⋅10-8 W/m2K4

ω [ - ] Dimensionless lengthξ [ - ] Molar ratio related to initial molar concentrationψ [ - ] Dimensionless width of the char reaction frontsuperscript0 Coordinates for the case of no shrinking* Integration variable, or if combined with the specific enthalpy i at the

surface of the particle// Per unit area, cross-sectional area for two-phase system and

particle surface area for discrete particles/// Per unit volume

subscriptA, B Auxiliary variableO2, H2, … Oxygen, Hydrogen, …a Ashb Boundaryc Charconv Convectioncond Conductiond Diffusion, or dry fueleq Equivalentg Gasi Gas species (O2, N2, H2O, ....)in Inert particlesj Fuel component (s,j) (moisture, volatiles, char, ash),

layer in particle (p,j) (wet fuel, dry fuel, char residue, ash),combustion stage (b,j) (drying, devolatilization, char combustion,particle surface)

k Counter

19

m Moisturep Particler Reactionrad Radiations Solidsc solid in fibre wall inside the charsd solid in fibre wall inside the woodv Volatilesw Water0 Initial condition, or starting position

Literature

1. Adams, T. N., Combust. Flame, 39:225 (1980).

2. Purnomo, Aerts, D. J., Ragland, K. W., Twenty-Third Symposium (International) on Combustion, TheCombustion Institute, Pittsburgh, 1990, p. 1025.

3. Hobbs, M. L., Radulovic, P. T., Smoot, L. D., AICHE Journal, 38:681 (1992).

4. Bryden, K. M., Ragland, K. W., Energy & Fuel, 10:269 (1996).

5. Thunman, H., Leckner, B., Fuel loading of a fluidised bed combustor, (W. Leuckel, J. Ward, R. Collin,and A Reis Eds.), INFUB, Portugal, 1997.

6. Shin, D., Choi, S., Combust. Flame, 121:167 (2000).

7. Di Blasi, C., Chem. Eng. Sci., 55:2931 (2000).

8. Pyle, D.L., Zaror, C.A., Chem. Eng. Sci., 39:147 (1984).

9. Chan, W-C. R., Kelbon, M., Krieger-Brocket B., Fuel, 64:1505 (1985).

10. Alves, S. S., Figueiredo, J. L., Chem. Eng. Sci., 44:2861 (1989).

11. Melaaen, M.C., Num. Heat Transfer, 29:331 (1996).

12. Di Blasi, C, Chem. Eng. Sci., 51:1121 (1996).

13. Hansson, K-M, Pyrolysis of Large Particles of Biomass – Experiments and Modelling, Thesis for thedegree of licentiate of engineering, Department of Energy Conversion, Chalmers University ofTechnology, 2001.

14. Kita, T., Sugiyama, H., Kamiya, H., Horio, M., AIChE Symposium Series No. 303, 92:120 (1996).

15. Saastamoinen, J. J., Richard, J-R., Combust. Flame, 106:288 (1996).

16. Roberts, A. F., Combust. Flame, 14:261 (1970).

17. Kanury, A. M., Combust. Flame, 18:75 (1972).

18. Reina, J., Vole, E., Puigjaner, L., Ind. Eng. Chem. Res., 37:4290 (1998).

19. Thunman, H., Niklasson, F., Johnsson, F., Leckner, B., ‘Composition of volatile gases and thermo-chemical properties of wood for models of combustion and high temperature gasification’, Submittedfor publication, March 2001.

20

20. Evans, D. D., Emmons, H. W., Fire Research, 1:57 (1977).

21. Pomerantsev, V. V. Ed., Fundamentals of applied theory of combustion, (In Russian), EnergatomizdatPublishing House, Moscow, 1986.

22. Janse, A. M. J., de Jonge, H. G., Prins, W., van Swaaij, P. M., Ind. Chem. Res., 37:3909 (1998).

23. Dasappa, S., Experimental and modeling studies on the gasification of wood-char, Academicdissertation, Department of Mechanical Engineering, Indian Institute of Science, Bangalore India, July1999. Parts of the work are published in the proceedings of the Twenty-Fifth and Twenty-SeventhSymposium (International) on Combustion, The Combustion Institute, Pittsburgh, 1994, p. 1619 and1998, p. 1335.

24. Palchonok, G., Heat and Mass Transfer to a Single Particle in Flidized Bed, Academic dissertation,Department of Energy Conversion, Chalmers University of Technology, Göteborg Sweden, ISBN 91-7197-712, 1998.

25. Bird, R. B., Stewart, W. E. Lightfoot, E. N., Transport Phenomena, John Wiley & Sons Inc., NewYork, 1960.

26. Thunman, H., Leckner, B., ‘Thermal conductivity of wood during different stages of combustion’,Submitted for publication, February 2001.

27. Kanury, A. M., Introduction to Combustion Phenomena, Gordon and Breach Science Publisher, NewYork, 1977.

28. Incropera, F. P., DeWitt, D. P., Fundamentals of Heat and Mass Transfer, Fourth edition, John Wiley &Sons Inc., New York,1996.

Appendix AThe mass and heat transfer coefficients are estimated from the maximum values obtained in afluidised bed [24]. In [24] a correlation is developed, which is valid over a large range ofparticle sizes, based on measurement data and empirical correlations from various authors.The Nusselt number, Nu, and the Sherwood number, Sh, are related to the inert sphericalparticles in a fluidised bed (index in) and are expressed for two extreme cases: the size of thefuel particles is equal to the inert particle (index A) or they are much larger than the inertparticles (index B),

0.67

,

, ,

Nu Nu

Nu Nuin in B in

in A in B eq

d

d

−= −

(41)

0.67

,

, ,

Sh Sh

Sh Shin in B in

in A in B eq

d

d

−= −

(42)

where index eq stands for equivalent. The mass and heat transfer coefficients are thencalculated as

Nu /g inh k d= (43)

d,0 = Sh /g inD dβ (44)

Nusselt and Sherwood numbers for fuel particles of the same size as the inert particles are,

21

0.39 0.33,Nu 6 0.117Ar Prin A in= + (45)

0.39 0.33,Sh 2 0.117Ar Scin A mf inε= + (46)

and for fuel particles much larger than the inert particles

0.19 0.5 0.33,Nu 0.85Ar 0.006Ar Prin B in in= + (47)

0.5 0.33,Sh 0.009Ar Scin B in= (48)

where Pr is Prandtl number, Ar Archimedes number, εmf bed voidage at minimumfluidisation, and Sc Schmidt number. The Archimedes number, Ar, is based on the inertparticles as

( )3

2

in in g

ing g

gdAr

ρ ρν ρ

−= (49)

The equivalent diameter of the fuel particles deq, is given by the surface area of the particle,Γb,a,

( )1/ 2

, /eq b ad π= Γ (50)

The mass transfer coefficients are compensated by a reduction factor, bd, for gas flowing outfrom the particles during drying and devolatilisation. No corresponding reduction of the heattransfer coefficient is made, as the major part of the heat transfer depends on particleconvection (and radiation). However, the heat transfer coefficient is reduced by a factorbecause the particles tend to float on the surface of the bed during the experiments. In [24] areduction factor for this combustion situation of 0.85 is recommended. The reduction of themass transfer coefficient is derived for spheres, infinite cylinders and plates, according to[25]. Here, it is assumed that this reduction factor can be used also for finite cylinders andparallelepipeds. Thus,

( )0

0 0

/

exp / 1g dd

dd g d

ub

u

βββ β

= =−

(51)

( ), ,

8.314

2s g

g b k k ik i

T Tu R X

P

+ ′′ =

∑ ∑ (52)

where ug is the velocity of the gas flowing out from the surface of the particle. The physicalproperties, thermal conductivity, k, and kinematic viscosity, ν, of the gas are assumed to bethe same as for air. Empirical correlations, which are based on table values from [28], aregiven in Table 2.

Appendix B

The thermal conductivity, perpendicular and parallel to the fibre direction, is calculatedaccording to [26], from the conductivities and densities of dry fuel, liquid water, fibre wall,

22

and the solid part of the char, using information regarding composition of the fuel, conversionstage and shrinkage. Knowing these properties, the effective thermal conductivity can becalculated from an equivalent fibre structure in the wood and the char. Quadratic tubes withnormalised wall thickness and a moisture layer represent the fibres. The normalisedthicknesses of wall fibre, ωs, moisture layer, ωw, and gas layer are defined as,

( )( )( )( ) ( )

0.5

,1 ,2 ,1 2

0.54

, ,2 ,

1 1 / /

1 1 / / 1

s p p d

s j p p j d j nn j

Y j

ω θ θ ρ ρ

ω θ θ ρ ρ=

= − −

− − Σ >

= for(53)

( ) ( ) ( )( )( )

0.52

,1 ,1 ,1 ,2 ,1 2 1

,

1 1 / /

0 1

w s s p p d

w j

Y

j

ω ω ω θ θ ρ ρ

ω

= − − − −

>= for(54)

, , ,1g j s j w jω ω ω= − − (55)

where the second index on the normalized thickness indicates the combustion stage (virginfuel, 1, dry fuel, 2, char, 3 and ash, 4), index d on the density, ρ, indicates dry fuel and index 1moisture, 2 dry wood fibre, 3 char and 4 ash. The effective thermal conductivity perpendicularto the fibre direction is calculated from the minimum effective thermal conductivity for eachconversion stage derived for an equivalent fibre,

( )( )

1 1

,, , , ,, , 1 , , , ,

, ,

1 s js j s j w j g jeff j A s j s j w j g j

s j w s j w g rad

k kk k k k k k

ωω ω ω ωω ω ω

− − − = + + + + + +

(56)

and the maximum effective thermal conductivity

( ) ( )

1

, , ,, , 1

, , , , , , , ,1s j w j g j

eff j Bs j s j s j s j w s j s j w j w g j g rad

kk k k k k k k

ω ω ωω ω ω ω ω

− = + + + − + + +

(57)

The minimum Eq (56) and maximum Eq (57) thermal conductivities, (n=1), are combined inserial and parallel paths,

( )1 1

, , 1 , , , ,2 2

11 1

, , 1 , , , ,2 2/ /

eff j An eff j An eff j Bn

eff j Bn eff j An eff j Bn

k k k

k k k

+

−

+

= +

= +(58)

which gives the effective thermal conductivity at n=2 after combination of those of n=1,where n is a counter. The values obtained by Eq (58) over- and underestimate, respectively,the serial and parallel conduction paths. As n increases, the difference between the twoconductivities decreases. When n approaches infinity the two values become equal and aresulting effective thermal conductivity is obtained.

, , , , ,; eff j eff j A eff j Bn k k k∞ ∞→∞ = = (59)

Along the fibre the thermal conductivity is simpler to estimate, and pipes placed next to eachother represent the fibres. The effective thermal conductivity, can be modelled by a parallelpath

Paper VI

1

Composition of volatile gases and thermo-chemical properties of wood formodeling of fixed or fluidized beds

Henrik Thunman, Fredrik Niklasson, Filip Johnsson, Bo Leckner*

Department of Energy ConversionChalmers University of Technology

S-412 96 Göteborg, Sweden+46 31 7721430, +46 31 7723592 (fax)

email [email protected](Submitted for publication)

AbstractModeling of conversion of solid fuel in combustion or gasification systems needs adescription of the composition of the volatile gases that leave a fuel particle of typical size ina fixed or fluidized bed during devolatilisation. Much work has been published on releases ofvolatiles, but a general model of the composition of volatile gases and a comprehensivepresentation of the related thermo-chemical properties of the fuel are still missing. Here, asimplified model is presented whose structure is valid for any solid fuel. The model consistsof a heat and mass balance complemented by empirical data. The empirical coefficients haveto be specified for certain classes of fuel: the fuels treated in this paper are one type ofhardwood and one of softwood, having particle sizes in the range used in utility boilers. Thespecies in the volatile gases are represented by the time mean mass fractions of CO2, CO,H2O, H2, light hydrocarbons, and heavy hydrocarbons. In addition, a comprehensive set ofdata is presented for such properties of wood that are needed for modeling of conversion infixed and fluidized beds. The data are taken from the literature and from measurementscarried out in the present work.

IntroductionModels of solid fuel combustion devices, such as fixed and fluidized beds, tend to beextremely complex and time consuming. Therefore simplifications have to be found. Thepresent model aims at characterizing composition and quantities of the volatile gases leavingthe surface of non-isothermal fuel particles by means of a relevant number of gas species.Relevant number of species means species for the thermal process and for relatedcomputations. These components are readily outlined according to experience: CO, CO2, H2,H2O, light (non-condensable) hydrocarbons, and remaining hydrocarbons, here called lumpedhydrocarbons. The problem to be solved then consists in the determination of the quantities ofthese gases. Characterization of the volatile gases is most essential for fuels having a highvolatile content, since in this case an error made regarding the composition may have asignificant impact. A characterization can be formulated in a general way, but it needs someempirical correlations and fuel data. As an example, data for trunk wood will be employedhere and the empirical parts of the model will be specialized for this fuel. Similarinvestigations could produce the empirical input for other fuels.

The volatile gases from the moisture-free part of wood have already been represented invarious ways in models. For example, they are assumed to consist of a single equivalent gas 1,by a number of gases given by measurements 2, 3, 4 (the composition in 2, 3 was estimated frommeasurements 5). There are numerous publications describing the rate of devolatilization, thechar yield and the composition of volatile gases 6, 7, 8, 9, 10, 11, 12, 13, 14 15, 16. Most of the works

* Corresponding author

2

cited focus on devolatilisation, where the fuel is isothermally heated to a rather low finaltemperature, lower than the temperature in a combustor. The experiments have a main focuson the production of charcoals and/or pyrolysis oils. In contrast, here the interest is on“combustion-like” conditions, which means that devolatilization is controlled by internal heattransfer and the medium surrounding the particle has a higher temperature than that neededfor devolatilisation. Besides, if the particles are thermally thick, similar to typical fuels, andthe devolatilization takes place in a temperature gradient inside the particle. The volatile gasesmay be transformed on their way out of the fuel particle.

Due to measurement complications it is difficult to close the elemental species balance, andattempts have only been made in some work. Efforts in closing the energy balance have beenmade in even fewer cases, probably due to the difficulty in closing the species balance. Thereare exceptions, e.g. 10 where the closure of both the elemental species balance and the energybalance has been tried. However, the closure was not complete. When modeling a combustionor a gasification system the balance of the elemental species and the energy must be fulfilledin order to satisfy the conservation equations that describe the system. A closure model has tobe established that is valid during all conversion stages of the fuel. For this propose it isconvenient to express the energy conservation equation in terms of specific enthalpy. Bydoing so, the heat of reactions at temperatures that differ from the reference temperature, aswell as the energy balance over the system, are easy to obtain. This is what is done in presentwork, where heat and mass balances are used to formulate a model for evaluating thequantities of the gases leaving a devolatilizing fuel particle. The model requires thermo-chemical data of the fuel (virgin fuel, char, tar, etc) as input. These data are collected fromliterature sources and completed for wood particles of the sizes used in utility boilers byresults from measurements carried out in the present work.

TheoryThe specific enthalpies of the fuel particle and of the gases leaving the particle, as well as thecomposition of the gas, are needed in each step of the conversion to conserve the energyaccording to the first law of thermodynamics (applied to chemical reacting systems). Wood,used as fuel, usually has high moisture content, and consequently a major part of the gasesreleased from the wood is evaporated moisture. The other major part consists of volatilesreleased during devolatilization. Here, the main focus is on the gases released duringdevolatilisation, and all considerations below concern the moisture-free part of the wood.Wood consists mainly of carbon, hydrogen and oxygen. Other species can be neglected whenthe global system is considered. The specific enthalpy, h, of the wood at a referencetemperature, superscript 0, can be calculated from the lower heating value, H, of the moisture-free wood and the elemental analysis, given as the mass fraction, X, of respective species andrelated to the moisture and ash-free wood as,

( )

( )

2

2 2 2 2

2

2 2

2 2

2 2

,,0 0 0

, ,, 0

1

12

H woodC woodwood wood CO CO H O H O ash

C H

H wood O woodC woodO O ash

C H O

XXh H M h M h Y

M M

X XXM h Y

M M M

= + + − −

− + − −

(1)

M is molar mass and Y denotes mass fraction of volatiles, char and ash in the moisture-freewood. The lower heating value of the dry wood can be divided into two parts; one belonging

3

to the char and one to the volatiles including the heat of devolatilization (ash is consideredinert), as

( )0wood char char vol vol devH Y H Y H H= + − (2)

Under combustion-like conditions the ash-free content of char consists of nearly pure carbon.The specific heat, cp, of char is therefore assumed to be equal to that of graphite (given inTable 4). This is a common assumption 4, 17. To further simplify the calculations, since the ashcontent is small, the ash is assumed to have the same specific heat and specific enthalpy as thechar. With these assumptions the specific enthalpy of the char at temperature T becomes,

0 0 0,

ref

T

char char p C char C CTh h c dT h h h= + = − +∫ (3)

where the specific enthalpy at the reference temperature can be calculated from the lowerheating value and the elemental analysis of the char,

2 2

2 2

2 2

2

2 2 2 2

2

, ,,0 0

,, 0 0

2H char O charC char char

char char O OC H O char ash

H charC char charCO CO H O H O

C H char ash

X XX YH h M h

M M M Y Y

XX YM h M h

M M Y Y

= + + − + +

+ − − +

(4)

A common assumption, if the lower heating value and elemental analysis of char are notknown, is that the ash-free char consists of pure carbon (that is, XH2,char and XO2,char≈0). Thenthe specific enthalpy of char becomes equal to that of graphite, and the heating value of charcan be calculated from Eq. (4).

The heat of devolatilization is defined by,

( )0 0 0 0dev char ash char vol vol woodH Y Y h Y h h= + + − (5)

but the literature values are usually given at the devolatilization temperature. The major partof the devolatilization occurs in the temperature range 700 to 900K 10, and the heat ofdevolatilization reported in the literature has to be recalculated to the reference temperatureas,

( )( )0, , ,

dev

ref

T

dev dev p wood char ash p char p volTH H c Y Y c c dT= − − + −∫ (6)

The specific heat of wood has been measured. The heating value, specific enthalpy at thereference temperature and the specific heat of the volatile gases are estimated from thecomposition of the volatile gases as,

vol i ii

H Hγ=∑ (7)

0 0vol i i

i

h hγ=∑ (8)

4

, ,p vol i p ii

c cγ=∑ (9)

where γ is the mass fraction of species i in the volatile gases. The volatile gases was assumedto consist of CO, CO2, H2O, H2 CiHj, and CnHmOk, and,

2 2 21

i j n m kCO CO C H C H O H H Oγ γ γ γ γ γ+ + + + + = (10)

The light hydrocarbons, CiHj, mostly consist of methane and ethylene 10, 15, 16, 18. Allhydrocarbons except methane and ethylene are lumped together and referred to as lumpedhydrocarbons in the following. The elemental composition, lower heating value and specificheat of the lumped hydrocarbons, CnHmOk, can be roughly estimated from previousknowledge 19. The specific enthalpy of the lumped hydrocarbons at reference temperature canbe estimated from the heating value,

2 2 2 2 2 2

0 0 0 0

2 4 2n m k n m kC H O C H O CO CO H O H O O O

m m kh H nM h M h n M h

= + + − + −

(11)

There are five more unknowns in the system of equations formed by Eq. (1) to (11) than thereare equations. The balances of the elemental species give three additional equations,

( )

2

2

, , ,

,

1

i j n m k

i j n m k

C wood ash vol C vol char C char

C H C H OCOCOvol C char C char

CO CO C H C H O

X Y Y X Y X

Y n M Y XM M M M

γ γγγ

− = +

= + + + +

(12)

( )2 2 2

2 2

2 2

2 2

, , ,

,

1

22

i j n m k

i j n m k

H wood ash vol H vol char H char

C H C H O H H Ovol H char H char

C H C H O H H O

X Y Y X Y X

mY M Y X

M M M M

γ γ γ γ

− = +

= + + + +

(13)

( )2 2 2

2 2

2 2

2 2

, , ,

,

1

1 1

2 2 2n m k

n m k

O wood ash vol O vol char O char

C H OCO H OCOvol O char O char

CO CO C H O H O

X Y Y X Y X

kY M Y X

M M M M

γγ γγ

− = +

= + + + +

(14)

The final two equations needed are empirical correlations based on the most commonlymeasured species in combustion or gasification systems, carbon monoxide, carbon dioxideand total hydrocarbons. The correlations are expressed as the ratios of carbon monoxide tocarbon dioxide and light hydrocarbons (obtained from the measurements of the totalhydrocarbons) to carbon dioxide,

21 /CO COγ γΩ = (15)

22 /i jC H COγ γΩ = (16)

The balances of the elemental species, Eq. (12) to (14) the conservation of energy, Eq. (6)inserted in Eq. (2)and put equal to Eq. (7), together with the empirical ratios, Eq. (15) and(16), form a system of equations that gives the composition of the volatile gases γ. The systemof equations can be solved by a matrix operation as,

5

2

2 2

2 2

2 2

2

2

22

2 2

1 1 12 2 2 2

1

2

0 0 1/ 1/ / /

1/ 1/ 0 0 / /

/ 0 / / 0 /

0 0 1 0 0

0 0 0 1 0

i j n m k

i j n m k

n m k

i j n m k

i j

n m k

CO CO C H C H O

j mH O H C H C H O

kH O CO CO C H O

H O H CO CO C H C H O

H O

H

CO

CO

C H

C H O

M M i M n M

M M M M

M M M M

ζ ζ ζ ζ ζ ζ

γγγγγ

γ−Ω

−Ω

=

2 2

2 2

,

,

,

1

/

/

/

0

0

C vol C

H vol H

O vol O

X M

X M

X M

κ

−

(17)

where ζ and κ are equivalent heating values. ζ is related to the lower heating value of thespecies in the volatile gases and is defined,

,

dev

ref

T

i i p iTH c dTζ = + ∫ (18)

κ is related to the lower heating value of the volatile gases and is defined,

( ) , , /dev

ref

T

i i wood char char dev char ash p char p wood volTi

H Y H H Y Y c c dT Yκ γ ζ = = − + − + − ∑ ∫ (19)

MeasurementsIn order to get the wanted properties of wood particles having sizes as used in utility boilers,single wood particles of these sizes were pyrolysed in an inert atmosphere, followed by aburnout of the remaining char. The composition of gas components was continuouslymeasured during the experiment.

The fuel particles to be analyzed were prepared from raw wood of birch (hardwood) and ofspruce (softwood) with material properties as shown in Table 1. Parallelepipeds of eight sizeswere tested (the total number of samples was 57). The particles were cut with the long side,varied between 10 and 40 mm, along the fiber direction of the wood and with the shortest end,varied between 3 and 10 mm, always in the perpendicular direction. The sizes were chosen tocover the range of specific areas (surface-area to volume ratios), 320-800 m-1, that is expectedto occur in a batch of forest waste wood as fired in utility boilers. Each wood-particle size wastested for birch and for spruce, as received (wet) and after drying for 24 hours in an oven at377 K.

The experiments were performed in a laboratory-scale fluidized bed reactor, as outlined inFigure 1. The reactor consists of a vertical quartz tube with a height of 1400 mm and an innerdiameter of 64 mm. The quarts glass tube extends 50 mm on each side of the insulated part ofthe reactor. The fluidized bed material (silica sand) rests on a distributor plate made of aporous quarts filter, placed nearly at half height of the quartz glass tube. Three separateelectrical heaters control the reactor temperature, dividing the reactor into three zones, asshown in Figure 1. The entering fluidizing gas flow, controlled by mass flow regulators, ispreheated in Zone I before passing the gas-distributor plate to the fluidized bed in Zone II andthe freeboard in Zone III. The reactor is designed for a maximum temperature of 1473 K.

6

Table 1. Properties of fuel used in themeasurements

Birch/Char Spruce/CharAsh (% mass, dry) 0.3/2.0(a) 0.4/2.0(a)

Density (kg/m3) 540±40/- 420±40/-H (MJ/kg) 18.4/33.6(b) 18.8/33.2(b)

ElementalAnalysis(c)

C 49.2/93.6 50.2/92.6O (by difference) 44.3/5.1 43.5/6.4H 6.3/0.7 6.3/0.8N 0.16/0.45 0.10/0.23S <0.01/ - <0.01/ -(a) calculated, (b) ash free, (c) % mass, dry ash freefuel

Table 2. Operating conditions of thefluidized bed reactor

ParameterOperatingCondition

Remark

Reactor Temperature 1123KConstant alongreactor

Density of bedmaterial

2600 kg/m3 Silica sand

Mean diameter of bedmaterial

0.30 mm

Bed height 80 mm At restSuperficial gasvelocity

0.60 m/s At 1123 K

Residence time of gasin reactor (bed to exit)

1.1 s At 1123 K

The top and the bottom of the glass tube reactor are water-cooled to prevent the gas inlet andoutlet connections to become overheated and to reduce the temperature of the exiting gas toaround 460 K. The fuel pieces were dropped down onto the fluidized bed from the top of thereactor tube. During the heating of the particle, including drying and pyrolysis, the fluidizinggas in the reactor was pure nitrogen, allowing the study of the composition of the pyrolysisgas. When the pyrolysis had finished, the fluidizing gas was changed to air in order to burnout the char residue in the bed. The mass flow controllers used allow any ratio of oxygen tonitrogen during combustion of the test samples. The operating conditions are listed in Table 2.For the condition in the experiments the Biot number was above 6 for all particle sizes, whichmeans that the heating of the particles is controlled by internal heat transfer and the choice ofreactor for the experiments does not affect the results.

The experimental set-up, including the gas-analysis system, is shown in Figure 2. The gas-analyzers are listed in Table 3. Calibration of the analyzers was performed daily before theexperiments. The residence time of the pyrolysis gases in the hot reactor was around 1 second.The gas was sucked out close to the reactor outlet, where two parallel fiberglass filters, kept at423K, filtered the gas. About 4 liters per minute of the sample gas was lead to an FTIRinstrument by heated tubing, passing a second filter and a heated pump into the test cell of theinstrument. Another part of the sample gas was lead by heated tubes to a total hydrocarboninstrument, measuring the hydrocarbons as methane equivalents by a flame ionizationdetector (FID). The third line of sample gas was lead to a dryer and a pump before beingdistributed between two CO/CO2 instruments and one O2 instrument. One of the CO/CO2

instruments was fed by sample gas diluted with nitrogen to avoid that the gas concentration ofCO out from the reactor exceeded the instrument’s maximum. The dilution factor wasestimated by comparison with CO levels measured below maximum concentration. The levelsof CO2 were then used to verify the dilution factor. CO was preferred for the estimation of thedilution factor, because the concentration of the diluted CO2 occasionally exceeded the lowerrange of the CO2 analyzer.

7

The integrated gas flow of each species is calculated to estimate the time average ratios of thedifferent gaseous species during devolatilization. The flow of the single species is estimatedfrom the measured concentration and the total gas leaving the reactor. The total gas is the sumof the gas flow of inert gas into the reactor, given by mass flow regulators, and the gasproduced during drying and devolatilization. The gas produced in the reactor is estimatedfrom the mass leaving the fuel particle and is correlated to the concentrations of the measuredspecies.

The fuel particles were to a large extent floating on the surface of the fluidized bed, andespecially larger birch particles fell apart at the end of devolatilisation phase. There was asmall amount of soot and tar on the outlet tube walls, but no condensed tar was observed tofall back into the reactor. No tar, but soot and small sand particles could be seen on the filters.

Property data for modelingThe empirical ratios of Ω1 = CO/CO2 and Ω2 = CiHj/CO2 in the volatile gases are estimatedfrom the experiments and from literature data 3, 15, 16. Literature data 3 give a ratio of Ω1

between 0.4 and 0.95 at 1092 K, and a temperature dependent ratio 16 expressed as

6 1.871 1.94 10 T−Ω = ⋅ (20)

which, in the temperature range of 665 to 990 K, is between 0.37 and 0.78.

The present measurements, Figure 3, show a ratio that increases linearly from around 2.4 to3.4, as the specific area of the fuel particle increases from 320 to 800. The difference is smallbetween the tested hardwood and softwood or between dry and wet particles. The high ratio,around 3, of CO to CO2 agrees with what has been found for rapid pyrolysis (1000K/s) ofsmall hardwood particles, (45-88µm) 10.

In the literature the ratio of the light hydrocarbons to CO2 is stated to be between 0.29 and0.46 3. A temperature dependent ratio has been expressed by 16,

11 3.39 14 4.072 1.305 10 3.007 10T T− −Ω = ⋅ + ⋅ (21)

in which the first term represents the ratio of CH4 to CO2, and the second term the ratio ofC2H4+C2H6 to CO2. This ratio of Ω2 is between 0.06 and 0.24 in the measured temperaturerange of 665 to 990 K. The present measurements give a ratio of THC to CO2 between 1.2and 1.7 (the THC measured on a gas cooled to 423K), depending on the specific area of thefuel, as illustrated in Figure 3. The ratio increases linearly with the specific area, for smallspecific areas, but for larger the ratio tends to become constant. No significant differencebetween wet or dry fuel or between hardwood and softwood can be seen. THC is expressed asmethane equivalents. The THC analyzer (FID-type) counts the carbon atoms in thehydrocarbons, related to the calibration gas. The actual concentration of the differenthydrocarbons is calculated from effective carbon numbers. The number is unity for methane,0.95 for ethylene and ethane, and 0.89 for benzene (information in the manual of the FIDanalyser). Assuming that the effective carbon number is the same for the lumpedhydrocarbons as for benzene, the ratio of THC to CO2 can be expressed as,

8

I I

II II

III III

(1)

(2)

(3)

(4)

(6)(6)

(5)

50

50

650

1400

65

Figure 1. Outline of the reactor, (1) gasoutlet, (2) gas inlet, (3) insulated casing,(4) quartz glass reactor tube, (5) distributorplate, (6) heaters in different zones I, II,III.

300 600 900

10

14

18

22

Specific Area [1/m]

Cha

r Yie

ld [%

]

300 600 9002.0

2.5

3.0

3.5

4.0

Specific Area [1/m]

CO

/CO

2 (b

y m

ass)

300 600 9000.8

1.0

1.2

1.4

1.6

1.8

Specific Area [1/m]

TH

C/C

O2

(by

mas

s)

300 600 9000.8

1.0

1.2

1.4

1.6

1.8

Specific Area [1/m]

H2O

/CO

2 (b

y m

ass)

Figure 3. Ratios of THC to CO2, CO toCO2 and H2O to CO2, and char yield,related to the specific area of the woodparticles, birch (wet, +, dry, *, solid trendlines), spruce (wet, o, dry, ∇, dashed trendline).

Table 3. Gas analyzers used

Analysed Gas Instrument Range

COCO2

Rosemount,BINOS® 100

0 – 3.0 %0 – 20 %

THCJ.U.M. Engineering,FID 3-300A

0 – 10% (CH4)

O2Leybold-Heraeus AG,Oxynos-1

0 – 25 %

H2OFTIRBomem MB 100

CO/CO2

CO/CO2

THC

O2

FTIR

Stack

Heated TubeHea

ted

Tub

e

FilterFilter

Filter

MFC

Nitrogen for dilution

gasdryer

Stack

MF

C

MF

C

Nitrogenor air

Oxygen

Flu

idis

ed B

ed R

eact

or

Figure 2. Experimental set-up and gas-analysis system, MFC stands for mass flowcontroller.

Table 4. Summary of thermo-chemicaldata for wood

Trunk wood Range Reference

Hwood (MJ/kg) 17-1-20.8 20

CHiOj; I 1.32-1.61(a) 20

J 0.56-0.64(a) 20

cp,wood Eq. (24) to (25)21, 22, 23,

24

Char Range Reference

HChar (MJ/kg) Eq. (26) 33

(Birch Ychar=14%) 32.9 (b)

(Spruce Ychar=20%) 32.5 (b)

CHiOj; i 0.07-0.17 (b)

J 0.004-0.055 (b)

cp,char (kJ/kg·K) Graphite, Table 5 4, 17

Devolatisation Range Reference

Hdev (MJ/kg) >623 K 0.20 to 0.25 26

Light hydrocarbons Range Reference

HCiHj (MJ/kg) 49.2 - 49.4(a) 37

γCH4 /γC2H4⇒ CiHj 2-3 (b)

cp,CiHj (kJ/kg·K) CH4, Table 5 (b)

Lumped hydrocarbons Range Reference

HCnHmOk (MJ/kg) 26-40 (b)

CnHmOk; n 6 12, 3

m 6.2 or 8 2 or 3

k 0.2 or 1 2 or 3

cp,CnHmOk

(kJ/kg·K)C6H6, Table 5 38, (b)

(a) calculated from ref., (b)obtained in present work

9

44 2 4 4 2 4

2 2

*,, ,

2 , ,

0.89 /1.90 /n m k n m kC H O vol CH C H OCH vol C H vol CH C H

CO vol CO vol

nX M MX X M MTHC

CO X X

+≈ + (22)

where the non-condensable part of the lumped hydrocarbons at the temperature of the gasentering the analyzer is indicated with an asterisk. As stated above the light hydrocarbons inthe ratio Ω2 are mainly methane and ethylene. This defines the ratio Ω2 as,

( )4 2 4 22 /CH C H COX X XΩ = + (23)

According to the definition Eq. (22) the ratio of THC to CO2 is always larger than the ratio ofthe light hydrocarbons to CO2, Eq. (23). To obtain the ratio of the light hydrocarbons to CO2

the mass fractions of methane and ethylene must be approximated from the ratio of THC toCO2, by Eq. (22). This is done by estimation of the ratios of methane to ethylene, and methaneand ethylene to the non-condensable part lumped hydrocarbons in the THC. The mass ratio ofmethane to ethylene is estimated to be between 2 and 3, 10, 15, 16, 18. On a molar basis thiscorresponds to 78-84% methane. (If the mass ratio is 3, an equivalent hydrocarbon takes theform, C1.16H4). The ratio of methane and ethylene to lumped hydrocarbons in the measuredTHC is estimated to be between 4 and 9. This ratio is based a qualitative judgment of theconcentrations of the non-condensable part of the lumped hydrocarbons at the temperature ofthe gas entering the THC-analyzer given by the FTIR-spectra that indicates that theconcentration of these lumped hydrocarbons is much smaller than the one of methane andethylene. With these estimates of the ratios of methane to ethylene and of methane andethylene to lumped hydrocarbons in the THC, the ratio of the light hydrocarbons to CO2, canbe approximated to be between 0.9 and 1.2 for the smallest specific areas and between 1.1 and1.5 for the largest. The specific heat of the light hydrocarbons is assumed to be close to that ofmethane, given in Table 5.

The ratios of CO to CO2 and of light hydrocarbons to CO2 obtained in the presentmeasurements are much higher than those of the other results quoted. To get the same ratio oflight hydrocarbons to CO2 as in the other quoted results, a major part of the hydrocarbons inthe THC must be related to the lumped hydrocarbons. This can, however, be excluded judgingfrom the qualitative measure given by the FTIR-spectra. The most likely reason for thediscrepancies is the difference in residence time in the heated part of the reactor. In themeasurements presented here, the residence time was around one second, whereas for thedata 16 the residence time in the reactor was around six seconds. The residence time in theother set of measurements 3 cannot be estimated. Rapid pyrolysis of small particles 10, wherethe composition of the volatile gases was measured after a short residence time, shows on aratio of CO to CO2 in the same region as the one reported here.

For measurements where the light hydrocarbons is estimated by a FID-analyzer, in a systemwithout FTIR, it would be better to cool the gases to ambient temperature before they enterthe THC analyzer. In this way as much hydrocarbons as possible is condensed, and thereby amore defined composition of the THC is obtained. If a FTIR is used, and the majorcomponents are measured from the FTIR-spectra, then it is an advantage to measure the THCat the highest possible temperature, because then an additional control of the mass fractionsgiven by Eq. (17) is achieved. This control involves the ratio of the THC to CO2 given by Eq.(22), using mass fraction of light and lumped hydrocarbons from Eq. (17), that must be largerthan or equal to the measured ratio of the THC to CO2.

10

A ratio of the water vapor to carbon dioxide concentrations in the pyrolysis gases can beobtained from the FTIR measurements of water vapor formed during devolatilization of thedry wood particles. This ratio varied between 0.8 and 1.3, see Figure 3. The reliability of themeasurements decreases with a decreasing particle size, due to the relatively slow exchangeof gas in the measurement cell. The FTIR provided one measurement point every 7th secondand, as the time of devolatilization for the smallest particles is around 30 seconds, only 4 to 5measurement points were obtained for these particles. However, the ratio was rather constant,around 1.2 for spruce and 1.0 for birch.

The property data of most interest are heating values, structure of the compounds CHiOj, andspecific heats. These data are collected both from literature sources and from the presentmeasurements. The results are summarized in Table 4.

A database 20 of 25 types of wood allows determination of the heating value, Hwood andestimation of i and j in CHiOj, Table 4. For a particular kind of wood the range of variation ofthe heating value and the elemental composition is smaller than those given in Table 4. Thespecific heat of wood is temperature dependent and is represented by empirical correlationsfrom the literature, e.g. for dry wood (i) 21, (ii) 22 (a mean value of six reported correlations),(iii) 23 (taken from 17), (iv) 24,

,

,

,

,

4.206 37.7 ( )

4.607 132.8 ( )

3.867 103.1 ( )

2.45 531.2 ( )

p wood

p wood

p wood

p wood

c T i

c T ii

c T iii

c T iv

= −

= −

= +

= +

(24)

The first three correlations (i) to (iii) are close to each other, whereas correlation (iv), resultsin same specific heat at ambient temperature, but has a temperature dependence which isabout half of that of the others. Correlation (iv) is interesting, since data forming thiscorrelation show a linear temperature dependence of the specific heat until devolatilizationstarts at 553K, whereas data forming the other correlation only do not exceed 450 K. Smalldifferences between different woods can be expected, as they consist of different amounts ofcellulose, hemicellulose and lignin. The heat capacity of pure cellulose is similar to thespecific heat of wood, according to the three first correlations in Eq. (24), but has slightlyhigher temperature dependence 25. Moist wood has a greater specific heat than what would beexpected from the simple law of mixtures 22, 23, as a result of the energy absorbed by thewood-water bounds. This is represented by a correction term 23,

( )( ) ( )( )( )( ) ( )

, , 4190 / 1 / 1 / 1

23.55 1320 / 1 6191 / 1

p wet p wood moist moist moist moist

moist moist moist moist

c c Y Y Y Y A

A T Y Y Y Y

= + − + − +

= − − − −(25)

Under combustion conditions the char yield becomes 10-25% of initially dry mass 9, 14, 26, 27, 28.However, flash pyrolysis of small particles can give a char yield below 10% for temperaturesabove 800 K 10, 29. In the present measurements the char yield was estimated from of CO2

concentration, elemental carbon content in char, and airflow through the reactor during theburnout of the char. For large, dry birch particles, with a specific area of 320, the char yield isaround 16%, Figure 3, which is similar to a value reported in a previous investigation 30,where a char yield of around 14% for birch is reported at the same temperature as in the

11

present measurements for particles of a size of 10x10x70mm. The char yield declines nearlylinearly with particle size, and for birch particles with a specific area of 800 it becomesaround 11%. For wet, large particles the char yield is somewhat higher, but for smallerparticles the difference disappears. The same trends are observed for birch and spruce, but thespruce shows 30% higher char yield than the birch. According to the elemental analysis of thepresent measurements, Table 1, and from the literature 12, 28, the content of carbon in the ash-free char is higher than 90% on dry mass, hydrogen is in the range of 0.6-1.5% and oxygen,determined by difference, in the range of 0.5-6.4%. This yields an approximate elementalcomposition given in Table 4.

Empirical correlations have been published 31, 32, 33 for heating values of char related to theamount of fuel released as volatiles. The difference between the correlations is small 34. Oneof the correlations 33, for the range of the conversion (1-Yvol) between 1 and 0.17, is

( )6 616.7 10 2.93 10 /(1 ) ; 1 0.17char vol volH Y Y= ⋅ + ⋅ − − > (26)

For a char yield of 20%, (1-Yvol)=0.2, the resulting heating value becomes 31.3 MJ/kg. If(1-Yvol)≤0.17 the char is nearly pure carbon, and the heating value of the char is assumed tobe the same as for (1-Yvol)=0.17, which gives 34.0 MJ/kg. These data can be compared withthose in Table 4.

The composition of the lumped hydrocarbons is difficult to generalize, as it depends stronglyon temperature and residence time 19. Here, the primary product of devolatilisation inside theparticle is assumed to have a composition close to pyrolysis oils, produced in the temperaturerange of 700 to 900 K, where most of the devolatilization occurs under combustion-likeconditions. These pyrolysis oils have an elemental composition close to that of wood 10, 35,and a heating value between 22 and 26 MJ/kg 13, 36. As the gas passes out through the particle,it meets higher temperature and active char surfaces, which crack the pyrolysis oils. Theremaining lumped hydrocarbons that leaves the surface of the fuel particle contain more stablehydrocarbons than they did originally, for example, benzene, naphthalene and toluene 19.These hydrocarbons have a heating value around 40MJ/kg 37. The conclusion is that lumpedhydrocarbons leaving the fuel particle, produced during combustion-like conditions, have aheating value between 26 and 40MJ/kg. In Table 4 the composition is assumed to be roughlythe same as the molecule of tar. Judging from the different hydrocarbons in the lumpedhydrocarbons in Table 4, the heating value is most likely higher than 40 MJ/kg for oneproposed composition 2, and little less than 40 MJ/kg for another one 3.

Table 5. Specific heat, cp,i=a1+a2T+a3T2+ a4T

3+ a5T4, and enthalpy for gas species and

graphite

Species h0 a1 a2 (×103) a3 (×106) a4 (×109) a5 (×1012)(a) O2 0 811 411 -175 37.5 -2.97(a) N2 0 939 302 -81.0 8.23 -0.150(a) H2O -13.4⋅106 1612 740 -8.24 -38.5 4.84(a) H2 0 14400 -369 1620 -467 41.3(b) CO -3.95⋅106 982 139 138 -96.1 15.9(b) CO2 -8.94⋅106 508 1390 -899 274 -31.5(b) C1.16H4 (cp for CH4) -3.05⋅106 1086 3820 159 -682 141.2(b) CnHmOk (cp for C6H6) Eq. (11) -9.31 2290 -763 112 -4.01(b) Char (cp for graphite) Eq. (4) -334 4410 -3160 1010 -119

Correlations valid in the range (a) 273-4000K, (b) 273-3000K, error less than ±2%

12

Table 6. Data for sensitivity analysis, dots indicate the same value as in reference case A.

Variable\Case A B C D E F G H ICO/CO2 2.4 2.5 • • • • • • •CiHj/CO2 1.2 • 1.0 • • • • • •CH4/C2H4 3 • • 2 • • • • •Char (%) 15 • • • 16 • • • •n/k (CnHmOk) 30 • • • • 6 • • •n/m (CnHmOk) 0.97 • • • • • 0.75 • •(a)HCnHmOk

(MJ/kg) 37 • • • • • • 30 •(b)H2O/CO2 0.95 • • • • • • • 0.85(a) Calculates the ratio H2O/CO2

(b) Calculates heating value of CnHmOk

The specific heat of the lumped hydrocarbons can be approximated with that of benzene, asthe specific heat does not vary greatly for the hydrocarbons, which from experience areexpected to be present in the lumped hydrocarbons, and the approximately equivalentmolecule is close to that of benzene, see Table 4. This approximation has been madepreviously 38.

The temperature dependent specific heats, in the form of polynomial fits (based on literaturedata 39, 37 ), and the reference enthalpies of the gas species used in the model, are summarizedin Table 5.

Sensitivity analysis of measurementsAs the system of equations, solved by Eq. (17), is rather stiff, and as the resulting compositionof volatile gases easily can take unrealistic values, the influence of the uncertainty in themeasurements on the resulting prediction of the composition was analyzed by a sensitivityanalysis. The sensitivity analyzes was carried out for birch, having an elemental analysis anda heating value according to Table 1. The input data to the sensitivity analyzes, presented inTable 6, were varied in the range of uncertainties in the measurements on the largest particles,specific area of 320. The ratio of methane to ethylene was varied between 3 and 2 in thelumped hydrocarbons. The amount of light hydrocarbons in the THC was only approximatelyknown, and therefore the ratio Ω2 was varied in a wider range than that resulting from themeasurements of THC.

The composition of the lumped hydrocarbons in the base case, case A, Table 6, is equal to aproposed composition 2, C6H6.2O0.2, and the variation of the atoms of hydrogen and oxygenfollows another proposal 3, C6H8O. The heating value of the lumped hydrocarbons was variedbetween 30 and 37 MJ/kg. The measurements carried out here contain information on theratio of H2O to CO2, and an alternative system of equations can be established, where theequation of conservation of energy is replaced by the ratio ΩH2O/CO2 = γH2O/γCO2. Thealternative system of equations can be expressed in the same way as Eq. (17),

13

2

2 2

2 2

2

2

22 2

,

2 2

1 1 12 2 2 2

1

2

1

/

0 0 1/ 1/ / / /

1/ 1/ 0 0 / /

/ 0 / / 0 /

1 0 0 0 0

0 0 1 0 0

0 0 0 1 0

i j n m k

i j n m k

n m k

i j

n m k

CO CO C H C H O C vol C

j mH O H C H C H O

kH O CO CO C H O

H

H O

H

CO

COO CO

C H

C H O

M M i M n M X M

M M M M

M M M M

γγγγγ

γ

−

−Ω

−Ω

−Ω

=

2 2

2 2

,

,

/

/

0

0

0

H vol H

O vol O

X M

X M

(27)

The result of the sensitivity analysis is presented in Figure 4 to 6. The sensitivity analysis wasperformed with either the heating value of the lumped hydrocarbons given, according Table 6and Eq. (17), Figure 4, or with the ratio of H2O to CO2 given, according Table 6 and Eq. (27),Figures 5 and 6. In general, the sensitivity analysis shows that within the present measurementaccuracy one obtains a stable solution both for the species concentrations in the volatile gasesand for the heating value of the lumped hydrocarbons, when the composition of the volatilesis obtained from Eq. (27). The only parameter varied that leads to a pronounced deviation, isthe atomic ratio of carbon to oxygen in the lumped hydrocarbon, case F. A reduction of thisratio raises the mass fraction of the light hydrocarbons and of the hydrogen and lowers themass fraction of the lumped hydrocarbon, if the heating value is given according to Table 6. Ifinstead the ratio of H2O to CO2 is given according to Table 6, the heating value is lowered.The heating value of the lumped hydrocarbons is expected to become lower as the atomicratio of carbon to oxygen decreases, since in such a case there is relatively seen less carbonand hydrogen to oxidize. In general the sensitivity of the heating value of the lumpedhydrocarbons is greater than that of the mass fractions. An increase of the amount of lumpedhydrocarbons in the measured THC, (by a lower ratio of CiHj to CO2) shows a lower amountof light hydrocarbons (as expected), and a higher amount of hydrogen and in the lumpedhydrocarbons, which tends to lower the heating value of the lumped hydrocarbons. Even caseC shows some deviation, but it is mainly as expected due to the change of the ratio of CiHj toCO2.

0

10

20

γ H2O

x100

0

10

20

γ H2x1

000

0

10

20

γ CO

x50

0

10

20

γ CO

2x100

A B C D E F G H0

10

20

γ CiH

jx100

A B C D E F G H0

10

20

γ CnH

mO

kx100

Figure 4. Resulting species distribution inthe volatile gases from the sensitivityanalysis according to Table 6, speciesdistribution calculated by Eq. (17).(Observe the different scaling factors)

0

10

20

γ H2

Ox1

00

0

10

20

γ H2x1

000

0

10

20

γ CO

x50

0

10

20

γ CO

2x100

A B C D E F G I0

10

20

γ CiH

jx100

A B C D E F G I0

10

20

γ CnH

mO

kx100

Figure 5. Resulting species distribution inthe volatile gases from the sensitivityanalysis according to Table 6, speciesdistribution calculated by Eq. (27).(Observe the different scaling factors)

14

A B C D E F G I30

32

34

36

38

40

HC

nHm

Ok [M

J/kg

]

Figure 6. Resulting heating value fromspecies distribution given by Eq. (27)frominput data for the sensitivity analysisaccording to Table 6.

0

10

20

γ H2O

x100

0

10

20

γ H2x1

000

0

10

20

γ CO

x50

0

10

20

γ CO

2x100

300 600 9000

10

20

γ CiH

jx100

Specific area [1/m]300 600 9000

10

20

γ CnH

mO

kx100

Specific area [1/m]

Figure 7. Estimated composition ofvolatile gases, expressed as mass fractions,versus specific area, for birch (* solid line)and spruce (∇ and dashed line). (Observethe different scaling factors)

Analysis of measurementsThe measurements of the birch and spruce for specific fuel areas in the range of 320 to 780were analyzed with Eq. (17) to obtain the most likely mass fractions of the components in thevolatile gases. The empirical ratios and char yields from Figure 3, and the fuel propertiesaccording to Table 1 and 4 are input to Eq. (17). In order to get the most likely heating valueand the elemental composition of the lumped hydrocarbons, the measured data for birch andspruce were analyzed, similar to that was previously done in the sensitivity analysis. Thisanalysis results in a most likely heating value of the hydrocarbons of around 37 MJ/kg and aelemental composition of C6H6.2O0.2. The heating value of 37 MJ/kg for the lumpedhydrocarbons is lower than that stated above for the given elemental composition(>40MJ/kg), but the heating value cannot have a higher value without producing anunrealistic composition of the volatile gases. This resulting heating value is closer to the oneexpected from the other proposed elemental composition, C6H8O, but if this elementalcomposition is inserted it would result in an unrealistically low heating value.

The resulting quantities of in the volatile gases are presented in Figure 7 in the form of massfractions of the volatile gases related to the specific area of the fuel. The most likely resultobtained for each specific area is chosen. The analyzes shows nearly identical results for birchand spruce, except for the difference in moisture content. The most significant trend is the fallof the mass fraction of CO2 and the raise of that of the lumped hydrocarbons for increasingspecific area of the fuel. Also, the mass fraction of the light hydrocarbons tends to decline asthe specific area becomes larger. The data on Figure 7 indicate that the ratio of H2O to CO2

should increase with increasing specific area, but this contradicts the measurements, wherethe ratio was more or less constant. This is most probably due to the slow gas analyzer usedfor the measurement of H2O, making the measurement of H2O uncertain for the smallestparticles. If there would be an uncertainty in the measurement of H2O also for the largerparticles, this could be a reason for the low heating value of the lumped hydrocarbons.

15

In the quoted case 10, where the ratio of CO to CO2 was in the same order as the present one,although performed on thermally small particles, the amount of the lumped hydrocarbons wasmuch higher and the amount light hydrocarbons much smaller. This indicates that cracking ofthe lumped hydrocarbons could have occurred in the present measurements, which produced ahigh quantity of light hydrocarbons. The cracking is to a large extent expected to take placeinside the particles as the volatile gases flow out. Nevertheless, cracking of gases that alreadyhave left the particles cannot be excluded, but is most likely smaller, since the longerhydrocarbons that crack form more stable hydrocarbons on their way through the hot charsurfaces in the outer part of the fuel particles. The absence of hot surfaces (except the reactorwalls) in the reactor after the sand bed also limits the cracking. In the cases investigated theempirical data given here should be considered the best available, since the residence time issignificantly shorter than in the other quoted measurements on thermally large particles.

ConclusionsThe description of the volatile gases divided in a relevant number species, and leaving fuelparticles of such sizes that are found in fixed or fluidized beds, is essential for sub models incomprehensive models of combustion devices. The main condition for the model is thatmatter and energy are conserved. Due to the complexity of the transformation of the fuel, itbecomes excessively time-consuming to model the gas leaving the thermally large particlesby means of a set of reaction rates. Because of time restrictions a more simplified descriptionof volatile release is needed for comprehensive bed models. Here, a sub model is presented,whose structure is valid for any solid fuel. The model solves a system of six equations toobtain the six gas concentrations. The system of equations consists of three mass balances,one energy balance and two empirical ratios. In some cases, dependent on the available inputdata, the energy balance can be replaced by an additional empirical ratio, and the energybalance can be used for validation. The model includes empirical coefficients, and they haveto be specified for certain classes of fuel. Gases from devolatilization of the dry part of high-volatile fuel are assumed to consist of CO2, CO, H2O, H2, light hydrocarbons (mainlymethane and ethylene), and lumped hydrocarbons (that is, the remaining hydrocarbons). Themethod proposed is for estimation of the quantities of these gas components in a case when nodata are available, or for a measured set of data needed to be checked.

In addition to the empirical ratios, thermo-chemical properties of the fuel during its variousphases of conversion are needed. Therefore, measurements have been carried out to providedata that can be compared with data from literature. This collection of data is especiallyselected to suit combustion and high temperature gasification. The data are specialized towood. The measurements concern softwood (spruce) and hardwood (birch), but similarcollection of data can be established for other fuels as well.

The system of equations is analyzed for influence of uncertainties in input data. The resultshows that the most important parameter is the C/O ratio in the lumped hydrocarbons. Thisparameter affects the heating value of the lumped hydrocarbons. An estimate gives 37 MJ/kgin the most likely case, to be compared with around 40 MJ/kg for tar and 20 to 26 forpyrolysis oils. Heating values and specific heats for wood, char, hydrocarbons and other gasesare compiled.

Measurements were carried out with two types of wood. 57 parallelepipeds of different size,chosen to cover the expected range occurring in a batch of forest waste as fired in utilityboilers, were dried, pyrolysed and burned in a fluidized bed reactor operated at 1123 K under

16

internal heat transfer control. These results show a clear correlation between the size of thefuel, expressed as specific area, and several quantities such as char yield, ratios of CO to CO2,

and light hydrocarbon to CO2. As the specific area increases (size decreases) a nearly lineardecrease of the char yield and linear rise of the ratios of CO to CO2, and light hydrocarbon toCO2 can be seen. The lower char yield is accompanied by an increasing amount of carbonrelative to hydrogen and oxygen in the volatile gases, which, together with the two ratiosmentioned, affects the composition of the volatile gases, since it favors the lumpedhydrocarbons on the behalf of the carbon dioxide. The two tested woods, hardwood (birch)and softwood (spruce), show the same trends. The only differences are in the level of charyield and in amount of H2O in the volatile gases. Further work could involve other fuels and amore detailed investigation on the influence of temperature. In the present work the mostrelevant temperature for the application was studied.

AcknowledgmentThe Swedish National Energy Administration has supported this work financially. We thankDr. Lars-Erik Åmand at this department for helpful discussions and the Swedish NationalTesting and Research Institute (SP), for the use of their experimental equipment and their kindassistance.

NomenclatureH [J/kg] Heating value (lower), related to subscriptM [kg/mole] Molar massT [K] TemperatureX [ - ] Mass fraction based on ash-free substanceY [ - ] Mass fraction based on dry woodcp [J/kgK] Specific heat, (related to subscript)h [J/kg] Specific enthalpy, (related to subscript)h0 [J/kg] Specific enthalpy, at reference temperature 298 K and

ambient pressure (related to subscript)i Atoms of carbon in light hydrocarbons, or index indicating speciej Atoms of hydrogen in light hydrocarbonsn,m,k Atoms in equivalent lumped hydrocarbons, C, H and OGreekΩ [ - ] Mass ratio of two gas species in the volatile gasesγ [ - ] Mass fraction in volatile gasζ [J/kg] Equivalent heating value (auxiliary variable)κ [J/kg] Equivalent heating value (auxiliary variable)

Subscript

C, H, O, etc Carbon, Hydrogen, Oxygen, etc.ash Ashchar Chardev Devolatilisationi Speciesn,m,k Atoms in equivalent lumped hydrocarbonmoist Moisture (mass fraction on wet fuel)vol Volatiles

17

wood Dry wood

References(1) Shin, D., Choi, S. Combust. Flame, 2000, 121, 167-180.(2) Adams, T. N. Combust. Flame, 1980, 39, 225-239.(3) Bryden, K. M.; Ragland, K. W. Energy & Fuel, 1996, 10, 269-275.(4) Di Blasi, C. Chem. Eng. Sci., 2000, 55, 2931-2944.(5) Kaiser, E. R.; Friedman, S. B. in Incinerator and Solid Waste Technology, (P. E.

Stephenson; R. K., Hampton; E. R. Kasier, and C. O. Veley Eds.), published byASME, New York, 1975, 247-256.

(6) Roberts, A. F. Combust. Flame, 1970, 14, 261-272.(7) Kanury, A. M. Combust. Flame, 1972, 18, 75-83.(8) Beamont, O.; Schwob, Y. Ind. Eng. Chem. Process Des. Dev., 1984, 23, 637-641.(9) Chan, W-C. R.; Kelbon, M.; Krieger-Brockett B. Fuel, 1985, 64, 1505-1513.(10) Nunn, T.R.; Howord, J.B.; Longwell, J.P.; Peters, W.A. Ind. Eng. Chem. Process Des.

Dev., 1985, 24, 836-844(11) Scott, D.S.; Piskorz, J.; Bergougnou, M.A.; Graham, R. Ind. Eng. Chem. Res., 1988,

27, 8-15.(12) Figueiredo, J. L.; Valenzuela, C.; Bernalte, A.; Encinar, J. M. Fuel, 1989, 68, 1012-

1016.(13) Horne, P. A.; Williams, P. T. Fuel, 1996, 75, 1051-1059.(14) Reina, J.; Vole, E.; Puigjaner, L. Ind. Eng. Chem. Res., 1998, 37, 4290-4295.(15) Di Blasi, C.; Signorelli, G.; Di Russo, C.; Rea, G. Ind. Eng. Chem. Res., 1999, 38,

2216-2224.(16) Di Blasi, C.; Branca, C.; Santoro, A.; Gonzalez Hernadez, E., Combust. Flame, 2001,

124, 165-177.(17) Ragland, K. W.; Aerts, D. J.; Baker, A. J., Bioresour. Technol, 1991, 37, 161-168.(18) Åmand, L-E. Personal communication, Department of Energy conversion, Chalmers

University of Technology, Sweden, 2001.(19) Evans, R.J.; Milne, T.A. Energy and Fuels, 1987, 1, 123-137.(20) BIOBIB - A Database for biofuels; University of technology Vienna, Austria,

http://www.vt.tuwien.ac.at/biobib, 2001.(21) Koch, P. Wood Sci., 1969, 1, 203-214.(22) Skaar, C., Wood-Water Relations, Springler-Verlag, Berlin, 1988.(23) TenWolde, A.; McNatt, J.D.; Krahn, L. Thermal properties of wood and panel

products for use in buildings, DOE/USDA-21697/1, Oak Ridge National Laboratory,Oak Ridge, TN, 1988.

(24) Harada, T.; Hata, T.; Ishihara, S. J. Wood Sci., 1998, 44, 425-431.(25) Boutin, O.; Ferrer, M.; Lédé, J. J. Anal. Appl. Pyrolysis, 1998, 47, 13-31.(26) Roberts, A. F. 13th Symposium (International) on Combustion, The Combustion

Institute, Pittsburgh, 1971; pp 893-903.(27) Alves, S. S.; Figueiredo, J. L. Chem. Eng. Sci., 1989, 44, 2861-2869.(28) Della Rocca, P. A.; Cerrella, E. G.; Bonelli, P. R.; Cukierman, A. L. Biomass &

Energy, 1999, 16, 79-88.(29) Scott, D.S.; Piskorz, J. Can. J. Chem. Eng., 1984, 62, 404-412.(30) Hansson, K-M., Pyrolysis of large particles of biomass-Experiments and modelling,

Thesis for the degree of Licentiate of Engineering, Department of Energy Conversion,Chalmers University of Technology, Göteborg, Sweden, 2001, forthcoming.

(31) Brenden, J. J. Combust. Flame, 1967, 11, 437-439.

18

(32) Allan, F.J.; Cameron, D.E.; Lambie, D.A. Combust. Flame, 1966, 10, 394-396.(33) Roberts, A.F. Combust. Flame, 1964, 8, 245-246.(34) Roberts, A.F. Combust. Flame, 1967, 11, 439-441.(35) Piskorz, J., Scott, D.S., Radlein, D. Pyrolysis Oils From Biomass, ACS symposium

series 376, (J. Soltes and T.A. Milne Eds.), 1987.(36) Nurul Islam, M.; Zailani, R.; Nasir Ani, F. Renewable Energy, 1999, 17, 73-84.(37) TRC Thermodynamic tables - Hydrocarbons, (Frankel, M.; Hong, X.; Wilhoit, R.C.

Eds.), NSRDS-NIST 75-120, U.S. Government printing office, Washington, 2000.(38) Grønli, M, A Theoretical and Experimental Study of the Thermal Degradation of

Biomass, Academic Dissertation, The Norwegian University of Science andTechnology, ISBN 82-471-0009-6, 1996.

(39) Barin, I.; Platzki, G. Thermochemical data of pure substances, Weinheim, VCH,1995.

Paper V

1

Thermal conductivity of wood duringdifferent stages of combustion

Henrik Thunman, Bo LecknerDepartment of Energy Conversion, Chalmers University of Technology, S-412 96 Göteborg, Sweden

+46 31 7721430 (tel), +46 31 7723592 (fax), email [email protected](Submitted for publication)

AbstractThe effective thermal conductivity is one of the most important parameters for modelling ofthermo-chemical conversion of wood. It changes both with temperature and with conversionof the wood. There have been suggestions on modelling of this problem, together withmeasurements, in earlier works, especially for wet and dry wood, but for char the knowledgeis poor. Here, two principle models of effective thermal conductivity on the basis of the porestructure in wood are validated by a comparison with direct numerical simulation of the fibrestructure. The validation leads to a more general model, both for conductivity in theperpendicular and in the parallel direction relative to the fibres in the wood. A secondaryresult is that the thermal conductivity of the solid phase in the fibre wall of the wood can beevaluated for dry and wet fuel, from measurement data on effective thermal conductivity. Theeffective thermal conductivity can be estimated from given values of temperature, density andmoisture content of the wood. It can also be applied to pellets and chipboards. In addition, thegeneral model expresses the effective thermal conductivity of char, since the wood materialmaintains its fibre structure during conversion.

Keywords: Thermal conductivity, Wood, Modelling

IntroductionThe effective thermal conductivity is one of the most important parameters for modelling ofthermal conversion of wood. The effective thermal conductivity changes both withtemperature and with conversion of the wood, and it is therefore of importance to describethis behaviour for modelling of the progress of combustion. A model is derived to calculatethe effective thermal conductivity in parallel and perpendicular to the fibres in a fibrousmaterial, and this model is applied here to wood. Wood particles have their largest surfacearea parallel to the fibres in the wood structure. This makes the thermal conductivityperpendicular to the fibres most important. However, the thermal conductivity along the fibresis also of interest in some cases, for example in pellets or chipboard, materials with randomfibre orientation.

Much measurement data, especially on conductivities of wet and dry wood, can be found inthe literature. For example, the work of MacLean [1], is probably the largest single study evermade of thermal conductivity perpendicular to the fibres of different woods. Along the fibresmeasurement data are available, for example, in a review carried out by Grønli [2]. Thermalconductivity of chars from biofuels has been measured by, for example, Lee et al. [3], Evansand Emmons [4], Alves and Figueiredo [5].

As previously shown by Siau [6] and Saastamoinen [7], a model consisting of quadratic cells,where the conduction is evaluated along various paths in relation to the orientation of thecells, gives a good agreement with effective thermal conductivities measured perpendicular tothe fibres of wood. Along the fibre the thermal conductivity is much simpler to estimate,

2

pipes placed next to each other can represent the fibres, and the effect of the solids that cut offthe gas path in the ends of the fibres can be neglected, Siau [6].

TheoryAs the derivation of the conduction paths perpendicular to the fibres differs to some extentbetween the models of Siau [6] and Saastamoinen [7], a numerical simulation was made, inwhich the energy equation was solved for a large number of quadratic cells located in a matrixbetween two thin plates having a very high conductivity. Figure 1 shows the principle set-up.The energy equation for this case,

( ) 0ik T∇ ∇ = (1)

where index i indicates the conductivities of solid (i=s), moisture (i=w) and gas (i=g)constituting the porous body. The boundary conditions of the simulation are: constant surfacetemperature, T2, on one end of the matrix and constant heat flow, q(T1), on the other end. Theboundaries perpendicular to the matrix and to the plates were perfectly insulated. A quadraticcomputational grid with a smaller size than the width of the wall of the solid phase wasapplied. The temperature was calculated at the surface of the plate having the constant heatflow. The effective conductivity, keff, was then evaluated from the temperature difference andthe heat flow according to the definition:

( )( )( ) ( )1

1 2 1 1 2 1 22 2 / / effq y y y k y k T T−

= + + − (2)

where y1 is the height of a bounding plate and y2 height of the matrix. k1 is the thermalconductivity of the plates, assumed to be large (500W/mK). Additional simulations were

q (T1)

T2

ωg

ωs

ωw/2

Plate

Plate

y1

y2

y1

Figure 1. Model of fibre structure of wet wood. ωs is width of solid, ωw width of moisturelayer and ωg width of gas. For numerical validation the heat flux was calculated betweenboundaries having temperature T1 and T2. In the calculation not nine, but a large number ofcells were placed in the matrix.

3

Figure 2. Fibre structure of hardwood,Maclean [8].

Figure 3. Fibre structure of softwood,Howard [9].

a) b) c)

s

s s

ss

w

w wg

Flux

R1,s

R2,s R2,w

R3,s R3,w R3,g

1

1

2

3

2

s sw

s

s

s

s s

s

w

w

w

g

Flux

R1,s

R2,s

R2,w

R3,s

R3,w

R3,g

1 1232s

s

w s s w g

Flux

Rs,1 Rw,2 Rg,3

1 1232

w s

Bi

Bi

Ai

Ai

Bi+1

Ai+1

Bi

Ai

Bi Ai Bi+1

Ai+1

Ai+2

Bi+2

Figure 4. Paths of heat flux through thefibre represented by electrical circuits. a)and b) paths perpendicular to the fibrederived by Siau [6] and by Saastamoinenand Richards[7] respectively. c) pathsparallel to the fibre, derived by Siau [6]. Rstands for resistance, index 1,2,3 indicatethe different paths, and s,w,g, indicatesolid, water and gas.

Figure 5. The paths perpendicular to thefibre as derived of Siau [6] (A) andSaastamoinen and Richards [7] (B),combined in parallel and serial paths

4

made to consider the effects of size, shape and relative position of the perpendicular cross-section of the fibre. Rectangular shapes represented the cross-section of the fibres withdifferent height to length ratios and different wall thicknesses. When uniform cross-sectionsof fibres with various height to length ratios and wall thicknesses, were placed in straightrows and columns in a matrix, the effective conductivity could vary between two extremes;the elements of the wood structure could either be modelled as placed parallel or serial to eachother in the direction of the heat flux. The perpendicular fibre structure of wood, hardwood[8] Figure 2 and softwood [9] Figure 3, differs in size, but shape and wall thickness is ratherconstant. This was simulated with a matrix divided into sub-matrices, where each sub-matrixconsisted of uniformed sized cross-sections of the simulated fibres, but the size, shape andwall thickness varied between the sub-matrices. A number of simulations were made and theresult showed that the calculated effective thermal conductivities nearly coincided with theone obtained from the simulations using uniform quadratic cross-sections placed in straightrows and columns. This concludes that a uniform structure of quadratic fibres can represent amore complex one, as long as there is no systematic arrangement of non-quadratic cross-section of fibres in the wood. The result supports the modelling of thermal conductivity ofwood as a system of serial and parallel conduction paths. In the derivation of conduction pathsboth Siau [6] and Saastamoinen and Richard [7] assumed that the water remains on thesurfaces of the fibre wall in an even layer. The relative thickness of fibre walls and thethickness of the water layer are calculated from the volume occupied by the solid and thewater. The relative volume is estimated by the apparent density of the wood divided by thereal density of the solid and the moisture. Knowing the volume occupied by each componentand assuming the type of fibre structure, the normalised thickness, ω, of each layer in the porecan be calculated from the densities, ρ, of the fuel and the fibre walls and from the shrinkageof the particle. The shrinkage θ is the ratio of a volume element to its dry volume element. Fora quadratic cell structure, the thickness of each layer will be (the details of the derivation aregiven in Appendix A),

( )( )( )

( ) ( )

0.5

,1 2 1 2

0.54

, 2

1 1 / /

1 1 / / 1

s d

s j j d j nn j

Y j

ω θ θ ρ ρ

ω θ θ ρ ρ=

= − −

− − Σ >

= for(3)

( ) ( ) ( )( )( )

0.52

,1 ,1 ,1 2 1 2 1

,

1 1 / /

0 1

w s s d

w j

Y

j

ω ω ω θ θ ρ ρ

ω

= − − − −

>= for(4)

, , ,1g j s j w jω ω ω= − − (5)

where the first index is related to the solid (s), moisture (w) and gas (g), the second index j isrelated to the different stages of combustion: virgin fuel (1), dry fuel (2), char residue (3) andash (4). For the density j represents: water (1), solid fibre wall in the dry and the virgin wood(2), solid fibre wall in the char (3) and solid fibre wall in the ash (4). Siau [6] derived theeffective conductivity of the cell by three layers in parallel, Figure 4a, and thereforeunderestimated the conductivity, for conversion stage j,

( )( )

1 1

,, , , ,, , 1 , , , ,

, ,

1 s js j s j w j g jeff j A s j s j w j g j

s j w s j w g rad

k kk k k k k k

ωω ω ω ωω ω ω

− − − = + + + + + +

(6)

5

Saastamoinen [7] derived the cell in three layers in series, Figure 4b, and thereforeoverestimated the conductivity, for conversion stage j,

( ) ( )

1

, , ,, , 1

, , , , , , , ,1s j w j g j

eff j Bs j s j s j s j w s j s j w j w g j g rad

kk k k k k k k

ω ω ωω ω ω ω ω

− = + + + − + + +

(7)

The results from Eq (6) and (7), (n=1), are combined in serial and parallel paths, as illustratedin Figure 5,

( )1 1

, , 1 , , , ,2 2

11 1

, , 1 , , , ,2 2/ /

eff j An eff j An eff j Bn

eff j Bn eff j An eff j Bn

k k k

k k k

+

−

+

= +

= +(8)

which gives the effective thermal conductivity at n=2 after combination of those of n=1, n is acounter. The values obtained by Eq (8) over- and underestimate, respectively, the serial andparallel conduction paths. As n increases, the difference between the two conductivitiesdecreases. When n goes towards infinity the two values become equal to each other and aresulting effective thermal conductivity is obtained. This resulting conductivity is nearly thesame as the one obtained from the simulation.

, , , , ,; eff j eff j A eff j Bn k k k∞ ∞→ ∞ = = (9)

Along the fibre the thermal conductivity is simpler to estimate, pipes placed next to each otherrepresent the fibres. The effective thermal conductivity, can be modelled by a parallel path, assuggested by Siau [6], Figure 4c,

( )( ) ( )( ) ( )2 2 2 2, , , , , , ,1 1 1eff j s j s j s j g j w g j g radk k k k kω ω ω ω= − − + − − + + (10)

The effective thermal conductivity in the different layers in the particle is of most interestduring drying and devolatilisation, since the heat transfer in the particle drives both thesephenomena. The temperatures during this period are moderate and the pore diameter is small,which makes the radiative contribution to the effective thermal conductivity negligible.During char combustion, when drying and devolatilisation are ended, a high temperature(above 1400°C) can be attained, and then the radiative contribution has to be included.However, during this combustion stage the effective thermal conductivity is of minor interest,since diffusion of oxygen into the particle and reaction rate determine combustion of charand, together with the external heat transfer, the temperature of the particle. The radiativethermal conductivity can be approximated by, Hottel and Sarofim [10],

3163rad rad porek T dε σ= (11)

where εrad is the emissivity in the pores, σ Stefan-Boltzmann constant and dpore is anequivalent pore diameter in the wood.

A partially converted solid should have an effective thermal conductivity somewhere betweenthe values of the present (j) and the next (j+1) conversion stage. When modelling theintermediate stage it is important to consider all input parameters, such as shrinkage, density

6

and thermal conductivity of the solid fibre wall. The simplest approach is a linearapproximation of the thermal conductivity between the two conversion stages j and j+1 as,

( ) , 1 ,1eff i eff j i eff jk X k X k+= − + (12)

where Xj is the mass ratio of the component being converted and the initial mass.

In pellets and chipboards the fibres are nearly randomly oriented and the effective thermalconductivity becomes the same in all directions. From geometrical consideration, 2/3 of thefibres are perpendicular and 1/3 parallel to the direction of the heat flux, and the effectivethermal conductivity can be estimated by,

2 1, ,3 3eff r eff effk k k= +

ResultsThe thermal conductivity perpendicular to the dry fibre, ks,2, is estimated to 0.52 W/mK forthe solid material in the dry wood by a least-square fit of Eq (9) to measurement data fromMacLean [1] and other authors, reviewed by Grønli [2]. Parallel to the fibre the correspondingthermal conductivity, ks,2, is estimated to 0.73 W/mK from Eq (10) and measurementsreviewed by Grønli [2]. The density of the solid in dry wood, ρ2, is chosen to 1480kg/m3, Siau[6]. The conductivity and density of the solid in dry wood are assumed to be independent oftemperature. The density, ρ1=1000 kg/m3 and conductivity, kw−0.487+5.887⋅10-3T−7.39⋅10-

6T2 W/mK are used for the moisture in the wood, according to data for water, Incropera andDeWitt [11]. The thermal conductivity of gas is assumed to be the same as for air, which ismotivated by the small difference between the major components produced during drying anddevolatilisation: water vapour, CO, CO2, O2 and N2, Kanury [12]. However, duringdevolatilisation CH4 and especially H2 will be present in rather large quantities. These gaseshave a much higher conductivity and stronger temperature dependence than the other gases,and the effective thermal conductivity will be somewhat underestimated. The largest erroroccurs in the char layer formed during devolatilisation, as the volatile gases pass through. Forair, the thermal conductivity can be calculated from an empirical correlation based on tablevalues, Incropera and DeWitt [11], given in the temperature range 250 to 3000K, as follows,

3 4 7 2

10 3 14 4 17 5

7.494 10 1.709 10 2.377 10

2.202 10 9.463 10 1.581 10

gk T T

T T T

− − −

− − −

= − ⋅ + ⋅ − ⋅ +

+ ⋅ − ⋅ + ⋅(13)

There is good agreement between Eq (6) to (10) and the measurement data for dry wood,Figure 6, and for wet wood, Figure 7. The difference between the models, represented by Eq(6) to (7), is rather small. The difference becomes clear if one regards the heat conductivity ofthe solid in the fibre. Siau [6] has suggested this heat conductivity to be 0.43W/mK, butSaastamoinen and Richard [7] chose 0.6W/mK. If the values mentioned are inserted into theirrespective equations, there is an even better agreement than the one shown in Figure 6, but forhigh density fuels the error becomes noticeable. If these values are used, for example, toestimate the heat conductivity of pellets, which have a high density (1000-1300 kg/m3), thedifference between Eqs (6) to (7) can be more than 15 %.

When char is produced at a high heating rate and with a high final temperature, the resultingporous structure is nearly pure carbon, Figueiredo et al. [13], Della Rocca et al. [14]. It isassumed that carbon in the porous structure has the same thermal conductivity and density as

7

amorphous carbon, for which the conductivity, ks,3=1.47+0.0011⋅T W/mK and density, ρ3=1950 kg/m3, Incropera and DeWitt [11]. The thermal conductivity of the carbon in the porousstructure is assumed to be the same in the perpendicular and parallel directions relative to thefibre. The solid in the small quantity of ash is given the same density and conductivity as thecarbon in the char. For char it is not possible to estimate the thermal conductivity of the solidmaterial in the cell wall from available measurement data, as the data of Lee et al. [3], Evansand Emmons [4] and Alves and Figueiredo [5] are given without sufficient information on theexperimental conditions, but the reported values indicate that Eq (8) overestimates theconductivity, perhaps because the samples used for the measurements were not completelycarbonised.

ConclusionsComparison with measurements show that the model of effective thermal conductivityperpendicular, Eq (14), and parallel, Eq (10), to the fibres, Figure 6 and 7, can be used tocalculate the effective thermal conductivity for all kind of wood species from density,moisture content and shrinkage, parameters that can be measured easily. Knowing fromGrønli [2] that the wood maintains its fibre structure after devolatilisation the effectivethermal conductivities for char can be calculated from the same models. For char there is nocomprehensive work available in the literature on measurements of effective thermalconductivity, as it is for wet and dry wood, and this makes it necessary to assume the densityand the corresponding thermal conductivity of the solid material in the char. In present workthe solid in char is modelled by amorphous carbon, motivated by the high carbon content inthe char. The radiative contribution to the effective thermal conductivity can be neglected forcalculation of the thermal phases of conversion of wood, due to small pore diameters andmoderate temperatures during drying and devolatilization, which are the phases of conversionwhen the effective thermal conductivity is most important.

0 500 1000 15000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Dry density [kg/m3]

Hea

t con

duct

ivity

[W/m

K]

0 0.1 0.2 0.3 0.4 0.50

0.1

0.2

0.3

0.4

0.5

Calculated thermal conductivity [W/mK]

Mea

sure

d th

erm

al c

ondu

ctiv

ity [W

/mK

]

Figure 6. Heat conductivity of dry woodas a function of density. Conductivityparallel to fibre, Eq. (10) (solid line withdots), measured data, Grønli [2] (stars).Conductivity perpendical to fibre, Eq. (15)(solid line), Eq. (7) (dashed line), Eq. (6)(dotted line). Measured, MacLean [1](circles), Grønli [2] (rhombs).

Figure 7. Comparison of measured,MacLean [1], and calculated effectivethermal conductivity, Eq (16),perpendicular to the fibres in wood, with amoisture content of 7-45% (based on wetwood).

8

AcknowledgmentThe Swedish National Energy Administration has supported this work financially. Theauthors would like to thank Gennadij Palchonok, Department of Energy Conversion,Chalmers Technical University, for valuable discussions.

Appendix A

Derivation of the thickness of the solid walls and the water layer in a fibre is made fromgeometrical considerations. If the fibres are represented as quadratic tubes, the ratio of thearea of the solid in the perpendicular cross-section, As, to the area of the perpendicular cross-section of the fibre (solid + gas), Af, becomes equal to the volume ratio of the solid in thefibre wall, Vs and the fibre, Vf, which in its turn, is equal to the ratio between the apparentdensity of the fibre, ρf, , and the density of the solid in the fibre wall, ρs (assuming that thedensity related to the gas is negligible).

fs s

f f s

A V

A V

ρρ

= =

The density of the dry fuel together with the shrinkage coefficient and the stage of conversiongive the apparent density of the fibre,

( ), /f j j d nn j

Yρ θ θ ρ=

= ∑4

2

where the shrinkage is the ratio of the volume of the fibre during conversion stage j to thevolume of the dry fibre, conversion stage j=2. By normalizing the area of perpendicular cross-section, the normalized thickness of the solid wall becomes,

( ) ( )( ) ( )( ). ../ / /s f f f s f f sA A A A Aω ρ ρ= − − = − −

0 5 0 50 51 1

and for the gas volume,

( )( ) .

/g f s f sA A Aω ω= − = −0 5

1

For the virgin fuel (j=1), the solid wall in the fibre is divided into a solid and a liquid part, andthe apparent density of the fibre is then given by,

( ) ( ) ( ) ( ), / / / /f d d n d dn

Y Y Yρ θ θ ρ θ θ ρ θ θ ρ θ θ ρ=

= + = +∑4

1 2 1 1 2 1 2 1 1 2 12

In the virgin wood, conversion stage j=1, the moisture is assumed to stay on the surface of thesolid in an even layer, and the thickness of the solid layer then becomes,

( )( )( ) .

, / /s dω θ θ ρ ρ= − −0 5

1 2 1 21 1

the thickness of the moisture layer,

( ) ( ) ( )( )( ) .

/ /w s s d Yω ω ω θ θ ρ ρ= − − − −0 52

2 1 1 11 1

and the gas volume,

w s wω ω ω= − −1

9

NomenclatureA [m2] AreaT [K] TemperatureV [m3] VolumeX [-] Mass ratio massY [-] Fuel composition related to dry fuelk [W m-1 K-1] Thermal conductivityq [W m-2] Heat flowy [-] Height

Greek

εrad [ - ] Emissivityθ [ - ] Shrinkage coefficientρ [kg m-3] Densityσ [W m-2 K-4] Stefan-Boltzmann constantω [ - ] Dimensionless length

Subscripts

A Conductive paths, SiauB Conductive paths, Saastamoinend dryeff Effectivef Fibreg Gasi Component, solid, water, gasj 1,virgin fuel, 2,dry fuel, 3,char, 4,ash, special for density, water (1),

solid fibre wall, in dry and virgin wood (2), in char (3) and in ash (4)n Counterpore Porer Randomly oriented fibres, as in pellets or chipboardrad Radiations Solidw Water Parallel to fibre

References

1. MacLean, J. D., ‘Thermal Conductivity of Wood’, Transactions American Society of Heating andVentilating Engineers, 1941, 47, 323-354.2. Grønli, M, ‘A Theoretical and Experimental Study of the Thermal Degradation of Biomass’, AcademicDissertation, The Norwegian University of Science and Technology, ISBN 82-471-0009-6, 1996.3. Lee, C. K., Chaiken, R. F., Singer, J. M., ‘Charring Pyrolysis of Wood in Fires by Laser Simulation’,The Sixteenth Symposium (International) on Combustion, The Combustion Institute, Pittsburgh, 1976, pp1459-1470.4. Evans, D. D., Emmons, H. W., ‘Combustion of Wood Charcoal’, Fire Research, 1977, 1, 57-66.5. Alves, S. S., Figueiredo, J. L., ‘A Model for Pyrolysis of Wet Wood’, Chemical Engineering Science,1989, 44, 2861-2869.6. Siau, J. F., ‘Transport Processes in Wood’, Springler-Verlag, Berlin, ISBN 3-540-12574-4, 1984.

10

7. Saastamoinen, J. J., Richard, J-R., ‘Simultaneous Drying and Pyrolysis of Solid Fuel Particles’,Combustion and Flame, 1996, 106, 288-300.8. Maclean, J.D., ‘Preservative treatment of wood pressure mothods’, US Dep Agr Handbook 40, 160 pp,19529. Howord, E.T., Manwiller, F.G., ‘Anatomical characteristics of southern pine steamwood’, WoodScience, 1969, 2, 77-86.10. Hottel, H. C., Sarofim, A. F., ‘Radiative Transfer’, McGraw-Hill Book Company, New York, 1967.11. Incropera, F. P., DeWitt, D. P., ‘Fundamentals of Heat and Mass Transfer’, Fourth edition, John Wiley& Sons Inc., ISBN 0-471-30460-3, 1996.12. Kanury, A. M., ‘Introduction to Combustion Phenomena’, Gordon and Breach Science Publisher, NewYork, ISBN 0-677-02690-0, 1977.13. Della Rocca, P. A., Cerrella, E. G., Bonelli, P. R., Cukierman, A. L., ‘Pyrolysis of Hardwoods Residue:On Kinetics and Chars Characterization’, Biomass & Energy, 1999, 16, 79-88.14. Figueiredo, J. L., Valenzuela, C., Bernalte, A., Encinar, J. M., ‘Pyrolysis of Holm-Oak Wood: Influenceof Temperature and Particle Size’, Fuel, 1989, 68, 1012-1016.

Paper VI

Final reportMay 1999Page 1 of 79

Activity 3.1.3Modelling and verifying experiments

on the whole furnace

H.Thunman, L-E. Åmand, F. Ghirelli, B. LecknerDepartment of Energy ConversionChalmers University of Technology

S-412 96 Göteborg, Sweden

March 1999

EU-contract: JOR 3CT96 0059



Summary

A model has been developed for combustion of a fuel layer on a moving grate, whichcan be connected to a CFD-calculation for combustion and gas flow in the free-roomof the furnace. Special attention has been paid to formation and reduction of nitrogenoxides. The work has not looked at the formation and destruction of nitrogen oxidesby detailed chemistry, but on the conditions in the fuel layer and in the free-room.From these conditions the nitrogen chemistry has been modelled in a simplified way.To verify the calculations extensive measurements have been performed at a31MWth industrial moving grate furnace burning wood chips, in co-operation withKvaerner Pulping Power Division. The modelling of the whole furnace givesacceptable results for the gas flow and the reactions of the main species, such asoxygen, carbon monoxide, carbon dioxide and hydrocarbons. Especially good is theagreement in the upper part of the furnace. In the lower part of the furnace theagreement with measurements is not as good as in the upper part, which is a resultof the difficulty to define the fuel layer on the grate. This is a problem of determiningthe empirical data needed in the fuel layer model, which could not be established bythe measurements, due to practical measurement problems at the test facility. Themodelling of the nitrogen chemistry showed a limitation in the use of reducedmechanisms available for the CFD-calculation, especially at the low temperaturelevels that are present in a grate furnace operating with biofuels. The nitrogenchemistry in the fuel layer model shows that the region of devolatilization is the mostinteresting and that the biofuels have a great potential in themselves to reduce thenitrogen oxides to low levels.



Table of content

Page

1. Introduction 7

2. The boiler and the conditions for modelling and measurements 9

3 Measurement preparation 11

4. Modelling 15

5. The NOx modelling 38

6. Experimental 42

7. Results 43

8. Discussion and conclusion 73

9. References 76

Appendix

A. Composition of the volatile 77

B. Analytic solution for reactions controlled by mixing 78



1. Introduction

Grate-firing has been used to burn bio-fuels for many decades, particularly inthe pulp and paper industry, where the fuel is supplied together with the rawmaterial for pulp production or from wastes, such as bark. Later it also becameused in the furnaces of the district heating systems. The original design wasthe plane grate, but later sloping grates of various shapes and inclinationswere employed. These grates are quite sensitive to the adaptation of theinclination of the grate to the type of fuel. If the fuel does not fit properly, ithappens that too much fuel slides down the grate and ends up only partlyburned in the lower end. The most modern development, the reciprocatingsloping grate, solves this problem and allows a rather controlled movement ofthe fuel along the grate by means of mechanically controlled rods, constitutingthe surface of the grate, moving back and forth according to an adjustablescheme, thus allowing to control the speed of the fuel layer's movement alongthe sloping grate, Figure 1.1. This is the type of grate treated in the presentwork.

Previous development work has been directed to achieving a complete and reliablecombustion on the grate. During recent years, however, the emission limits havebeen lowered and a complete combustion is not a sufficient criterion of acceptableoperation: now a low emission of nitrogen oxides also has to be achieved at thesame time as the desire for complete combustion remains. These requirements havemade it necessary to improve the understanding of the combustion processes ingrate-fired furnaces, just as in other combustion devices. Tools to evaluate theoperation of the grate and to predict the behaviour of combustion and pollutantformation and destruction are needed. Much is also gained simply by an increasedqualitative understanding of the processes taking place, since the behaviour can beimproved by simply adjusting the existing grate for a certain fuel. Several parametersof adjustment are available: initial bed height, air distribution along the grate,movement of the grate (speed of the fuel layer along the grate), secondary air jets,flue gas re-circulation etc. This is, indeed, quite a complex situation that has to beassessed in addition to the design information needed for design of the unit.

The present work uses existing knowledge elements to develop a model of thecombustion behaviour of the fuel layer on a grate and its connection to the gas spaceabove the grate, the free-room with its secondary air jets and combustion in thegaseous phase. Moreover, special attention is paid to formation and destruction ofnitrogen oxides. This item can be treated either by detailed nitrogen chemistry or byassuming that the conditions in the fuel layer and free-room control the nitrogenchemistry. The latter approach is followed here. It is quite obvious, however, that theexisting knowledge on the behaviour of the fuel layer is not sufficient and that aconsiderable model development is needed. In the first place a fuel layer modelshould be developed to give input data at the lower boundary to a computerised fluiddynamic calculation of the processes in the gas space, including various reactionsand heat transfer. In this part of the furnace, in contrast to the fuel layer, availablecommercial programmes can be applied with advantage. In the present caseFLUENT is used. In order to validate the computational procedures and to obtain


additional information about the combustion process, measurements have beencarried out.

The measurements intend to describe the overall combustion behaviour inside thefurnace. Measurements are performed in several positions in the free-room and inthe gas flow entering and leaving the furnace. For the fuel layer only the velocity ofthe fuel layer along the grate and the surface temperature of the grate weremeasured. These measurements together with the boiler design data give the inputto the modelling and a base for validation of the simulation.

In summary, the present work consists of three parts: modelling of the fuel layer, free-room modelling and measurements predominantly carried out in the free-room and inthe furnace exit. The purpose of the work is to provide tools that could be used fordesign predictions related to fuel layer and free-room.

Figure 1.1 Reciprocating sloping grate (Kvearner)


2. The boiler and the conditions for modelling and measurements

The simulation concerns an existing 31MW grate-fired boiler that produces hot waterfor the district heating network of Trollhättan, designed and built by Kvaerner Pulping,Power division. The fuel used is wood waste from the pulping industry, consisting ofsplinters, bark and sawdust. The boiler is operated in the load range of 25 to 100%and with fuel having moisture content of 35 to 55% on mass basis. Due to the highlymoist fuel, the plant is equipped with a flue gas condensation unit to recover thelatent heat of the water vapour. Of the 31MW produced 6MW are delivered by thisflue gas condensation unit, 17MW by the convection area of the flue gas pass and8MW by the tube walls of the furnace. The wide fuel and load range of operationrequires a number of special design considerations. The fuel is supplied to the gratethrough two fuel chutes, covering the total boiler width. Raising or lowering ceramicbeams in front of the first section of the grate controls the height of the fuel layer. Thegrate is a reciprocating one consisting of a steel support with intermediate rollers onwhich the grate sections are placed. The sections are put into operation by means ofhydraulic pistons in the boiler front. All castings exposed to radiant heat from thefurnace are composed of a chrome/nickel alloy, capable of withstanding highoperation temperatures. The grate is built up of movable grate bars. A row of gratebars is alternating between fixed and moving every second. The velocity of the fuellayer along the grate is reduced significantly half way on the grate in order to burn outthe char. The primary air supply is divided into 2 times 5 air zones (P), see Figure2.1. Details of the grate are shown on Figure 2.2. The primary air-flow is preheated to150 °C and optimised for the combustion of the fuel layer above each wind-box. Arelatively high pressure-drop across the grate has been chosen to avoid blowing ofholes through the fuel layer. The combustion and pyrolysis gases evolving from thefuel layer are mixed by the recirculation gas jets (R in Figure 2.1) and the mixturepasses through the narrow section of the combustion chamber (the neck) where it ismixed with the secondary air (S in Figure 2.1) supplied in three rows. Each row ofsecondary air has a separate air-box with control valves. The high moisture contentof the fuel requires refractory lined walls and roofs below the neck in the furnace. Aflue-gas recirculation system is installed to improve the mixing in the lower part of thefurnace and to better control the combustion temperature, independent of themoisture content, which makes low NOx operation of the boiler possible.Downstream of the furnace, the flue gases are cooled down to a temperature of 170°C in the boiler back passes by the heat recovery surfaces. The fly ashes areseparated from the gas flow by an electrofilter. Condensation equipment humidifiesthe air to further increase the heat production. Technical data of the boiler are givenin Table 2.1.


Figure 2.1 Scheme of test plant, Kvaerner Pulping, Power Division.

Figure 2.2. The reciprocating sloping grate of the test boiler in Trollhättan.


Table 2.1. Technical data for the test facility in Trollhättan.

Maximum capacity 25 MWth

Maximum condensationcapacity

6 MWth

Moisture content of the fuel 35-55 %Boiler water temperatures 200-140 °CInlet district heatingtemperature

72 °C

Outlet district heatingtemperature

120 °C

Grate surface area 39.8 m2

Free-room volume 295 m3

Excess air 25 %Flue gas temperature 170 °CNOx 72 mg/MJCO 90 mg/MJDust (13% CO2 dry gas) 35 mg/Nm3

3 Measurement preparation

It was necessary to prepare the test facility in Trollhättan for the measurements in thepresent project. In order to get access to the boiler furnace with probes, 29measurement holes were taken up. Banisters were moved or taken away, termo-couples and pressure transducers were installed as well as cooling-water andsewage systems in connection to the measurement holes. For collection ofmeasurement data, signal cables were drawn from each of the measurement levelsto the control room were the data collection took place. A great number of otherpractical arrangements were also necessary for the measurements. Themeasurement holes had to be designed in different ways, depending on the tubewalls. The tube walls in the lower part of the furnace were prepared with large roundholes, Figure 3.1. Narrow rectangular holes were made in the fin between the tubesin the upper part of the furnace, Figure 3.2, in order to reduce the costs and to installmore holes. The rectangular holes restrict the measurement to probes having asimple cooling system. The positions of the measurement holes are presented inFigure 3.3.


Figure 3.2. View of rectangular holes and Figure 3.3 . View of the round holesequipment for guiding and fixing the with equipment for guiding and fixing theprobe. .probe.

Figure 3.1. The measurement holes in the test boiler in Trollhättan.

Four kind of probes were specially designed and built for the measurements:

• A cold suction probe for local gas concentration and temperature measurementsin the rectangular holes. With a cold probe is meant that the gas is cooled downto the temperature of the cooling water, Figure 3.5.


• A hot suction probe for local gas concentration measurements in the round holes.With a hot probe is meant that the gas is cooled down to a temperature of 200°C,Figure 3.6.

• A zirconia cell probe for local oxygen fluctuation and temperature measurementsto be used in the round holes, Figure 3.4.

• A flow direction probe, to be used in the upper part of the furnace, for examinationof the direction of the gas flow.

The cold suction probe measures the concentration of CO, CO2, O2, NOx and totalhydrocarbon concentration, THC (for analysis equipment, see Table 3.1). The hotsuction probe measures NH3 with a FTIR (Fourier Transform Infra Red) analyser,together with the same gas species as those measured with the cold suction probe.For the ammonia measurements, a hot suction probe must be used to preventabsorption of ammonia in the condensate. The arrangement to keep a rather highgas temperature is space consuming, and this restricts the ammonia measurement tothe round holes in the furnace.

Table 3.1. Gas analysers

Analyser Principal ofmeasurement

Manufacturer Measurementrange

Calibration gas

O2 Paramagnetic M&C PMA 10 0-30 % 9.97 %CO*

CO2

NDIR Binos 100 0-30000 ppm0-5000 ppm0-20 %

4040 ppm

12,0 %NOx chemiluminiscent Eco Physics 0-1000 ppm 91.7 ppm NOx

90.7 ppm NOTHC* FID FID-analyzer 0-30 000 ppm 899 ppm CH4NH3 FTIR Bomem MB 100*) When the concentration of CO and THC exceeded the range of the analyser, thegas concentrations were analysed by the FTIR.

Figure 3.4 The zirconia cell probe.


Figure 3.5 . The cold suction probe for gas concentration and temperaturemeasurements.

thermo-statedshell

heatedsamplingtube

ceramicfilter

Figure 3.6a . The front part of the hot gas extraction probe.

backflushtubes

Teflonelectricinsulator

heatedsamplingtube

low voltagehigh currenttransformer

220 VAC

Figure 3.6b . Rear part of the hot gas extraction probe.


4. Modelling

The present work uses existing knowledge to develop a model of the combustionbehaviour of the fuel layer on the grate and its connection to the gas space above thegrate, the free-room with its secondary air jets and combustion in the gaseous phase.Moreover, special attention is paid to formation and destruction of nitrogen oxides.This item can be treated either by detailed nitrogen chemistry or as controlled by theconditions in the fuel layer and free-room. The latter approach is chosen here, but itis quite obvious that the existing knowledge is not sufficient and that a considerablemodel development is needed. In the first place a fuel layer model should bedeveloped that gives input at the lower boundary to a computational fluid dynamics(CFD) calculation of the gas space, including various reactions and heat transfer. Inthis part of the work, in contrast to that related to the fuel layer model, availablecommercial programmes can be applied with advantage. In the present caseFLUENT/UNS 4.2.5. is used. This software package has built in the necessaryphysical models to simulate gas phase combustion (turbulent fluid flow, chemicalspecies mixing and reaction, conductive, convective and radiant heat transfer). Thepackage includes software for domain definition and discretization and has anintegrated nitrogen oxide reaction module.

The complexity of modelling of a whole furnace is obvious, and it is thereforeimportant that already from the beginning a realistic accuracy level is defined on whatshould be required from the overall solution. In the present work the knowledge onthe combustion of a moving fuel layer sets the limit. The understanding of thecombustion of the fuel layer is the key for the nitrogen chemistry, because a modernboiler is designed to prevent the formation of thermal NOx, the main source of NOx isfrom the combustion of the fuel. In the fuel layer the solid fuel is converted to gas,and the precursors of the pollutants are formed and transported up to the free-room.Since the detailed knowledge of the combustion of the fuel layer is not previouslyavailable, the present modelling has been focused on the combustion of this fuellayer. Special efforts have been made to model the parts that are important for theNOx chemistry. The fuel layer is exposed to a rather complex combustion situation,both the primary airflow and the velocity of the fuel layer along the grate changeseveral times while the fuel is transported along the grate. For the nitrogen chemistrythe position where the fuel-bound nitrogen leaves, the local oxygen concentrationand the height of the char layer are the main parameters. If the nitrogen is releasedat or close to the surface of the fuel layer, formation and destruction of the nitrogenpollutants will take place in the free-room above the fuel layer. If there is a char layer,both formation and destruction of nitrogen pollutants can take place in it, dependingon the oxygen level. In the reaction front passing through the fuel layer, precursors ofthe nitrogen oxidation will be released. Dependent on the oxygen level, theseprecursors will form or reduce nitrogen oxides as they pass through the char layer.

The models of the fuel layer and the free-room run independently of each-other; thefuel-layer model represents one of the boundary conditions for the free-room modeland vice versa. This requires an iterative calculation procedure to reach a convergedresult for the combustion inside the entire furnace. Convergence is attained when theheat flux to the fuel layer, given by the free-room calculation, agrees with the heatflux to the fuel layer given in the fuel layer model. Since a commercial programme is


used for the free-room, the fuel layer model has to be described in such a way thatthe output from the fuel layer and free-room model easily can be used for theiteration. The chemistry of combustion is divided into two parts called “mainchemistry” and “trace chemistry”. The main chemistry includes the reactions andspecies relevant for the determination of velocity and temperature fields, while thetrace chemistry includes species present at concentrations that may be neglected inthe heat and mass balances. The first part, requiring most computational time andpower, calculate the balance equations of the main variables: temperature, averagevelocity and concentrations of non-trace species. The trace chemistry is neglected inthis part. Subsequently, during the second part of the calculation, the postprocessing, the solution from the first part is fixed, and the balance equations for thetrace chemistry are solved. Therefore the post processing will not influence the mainfields. This separation of the chemistry is useful, and saves considerablecomputational time and power, which makes it possible to test several cases withdifferent emphasis on the trace chemistry on the same calculation.

Bed

hei

ght

Time or Length of grate

Reaction front

Char layer

Unreacted fuel layer

Surface layer

xs

xc

xr

xU

Primary air

HeatFlux

Figure 4.1. Illustration of the four layers; surface, char reaction front and unreactedfuel.

The calculation time of the fuel layer on the grate is important to limit the calculationeffort. Therefore the model of the fuel layer is simplified as much as possible. For thispurpose the fuel layer is split up in four characteristic layers, as illustrated in Figure4.1 surface layer, char layer, reaction front and unreacted fuel layer. The surface andthe char layers consist of char. This representation of the fuel layer is supported byexperiments in pot furnaces, e.g. Gort 1995, Saastamoinen 1999. The differencebetween them is that the surface layer, in contrast to the char layer, is influenced bythe conditions in the free-room above the fuel layer. The reaction front is the layerwhere drying and devolatilization take place, and the unreacted fuel layer consists ofthe fuel not yet reached by the reaction front. The most complex part of a fuel layermodel is the representation of the reaction front; a narrow layer where the fuel isdried and devolatilized simultaneously. In this layer the heat and mass transport iscomplex and a detailed model is required. Saastamoinen [1998], for instance, modelsthe behaviour of a single particle through the reaction front, but in the present work amore simplified approach is made. The heat and mass transfer components in the


reaction layer are qualitatively modelled by the radiation across the reaction layerand adjusted by fitting parameters. The fitting parameters give a qualitativedescription of the heat flow through the reaction front, the heat flow through singlefuel particles in the reaction front and the consumption of oxygen and gaseous fuelconstituents. The char layer is modelled in more detail. The fuel layer is divided into anumber of sublayers where the char particles are assumed to burn with a shrinkingcore. It is assumed that the reaction rate is controlled by diffusion of oxygen from thegas between the particles through the ash layer that builds up on the particle surfaceinto the char core. The height of the fuel layer is modelled by the continuity equationin one dimension. The height of the fuel layer decreases due to particle shrinkingduring the conversion of the fuel particles and rises due to the reduction of thevelocity of the fuel layer along the grate. The simplifications mentioned make itpossible to describe a model, which produces the necessary input to the free-roommodel at a sufficiently short calculation time, and gives the local condition for thenitrogen chemistry. Due to the fitting parameters of the reaction front someknowledge is needed about the combustion behaviour of the fuel layer on the grate,especially estimation on the time when the reaction front reaches the surface of thegrate. The fuel layer model is validated numerically by a molar and an enthalpybalance over the fuel layer.

Input data to the fuel layer model are given by the operation of the boiler, by theincident heat flux from the free-room above the fuel layer and of the fittingparameters in the fuel layer model itself. Data given by the operating condition are:type of fuel, fuel feed rate, initial height of the fuel layer, primary airflow and velocitydistribution of the fuel layer along the grate. The incident heat flux from the free-roomis given to the fuel layer model as an equivalent temperature distribution of theradiation, given by the free-room calculation. Fitting parameters are: relation betweenthe actual heat flux and the heat flux given by radiation over the reaction front,maximum heat flux into single particles, mixing rate of gas inside the fuel layer andminimum voidage in the fuel layer. The fuel layer model gives the flow rate,composition and temperature of the gas leaving the fuel layer. It also gives theheight, mass loss, and temperatures inside and on the surface of the fuel layer andthe position of the reaction front inside the fuel layer. In the Trollhättan boilermeasurements of the temperature on the metal surface of the reciprocating gratewere made and these measurement has been used to choose the fitting parametersin the fuel layer model.

4.1 Description of fuel layer model

Four layers; the unreacted fuel layer, the reaction front, the char and surface layerscharacterise the bed, Figure 4.1. The unreacted fuel layer consists of the fuelbetween the grate and the reaction front. The reaction front is located as the areawhere devolatilization takes place. The char reaction layer is the layer downstream ofthe reaction front. This layer is not influenced by the conditions above the bedsurface. The surface layer is the layer downstream of the reaction front and the charlayer, and this surface layer is influenced by the conditions above the bed surface. Byassuming that no heat transfer takes place in the unreacted fuel layer and that thereaction front is thin, the behaviour of the bed can be described by the velocity of the


reaction front and by the heat balance over the char and the surface layers. Tosimplify the calculation, the velocity of the reaction front is calculated for adimensionless height of the reaction front, x’U. This height is unity at the surface ofthe bed and zero at the grate. The velocity of the reaction front is obtained by dividingthe mass release per unit area in the reaction front, ∂mr/∂t, with the amount of fuelper unit area. The amount of fuel per unit area is calculated from initial mass of fuelper unit area, given by the fuel density ρF, and initial packing of the bed 1-ν0, and thebed height under the condition that the fuel keeps its size and that the packing isgiven by the initial bed height xb0 and the ratio between the initial and current velocityof the bed along the grate ub0/ub. If the fuel maintains its size and the bed keeps itsinitial packing the solution of the continuity equation in one dimension gives that theheight of the bed change proportionally to the ratio of the initial and actual velocityalong the grate ub0/ub. The change in bed height becomes

∂∂

= −−

∂∂

x

t

u

x u

m

tU

F

b

b b

r' 1

1 0 0 0ρ ν1 6(4.1)

The actual position of the reaction front xu, is the dimensionless height of the reactionfront and the bed height under the condition that the fuel maintains its size but notsits packing, xb.

x x xU U b= ' (4.2)

The solution of the continuity equation in one dimension for the bed height under thecondition that the fuel keeps its size but not its packing is,

x xu

ub bb

b

=−−0

0 01

1

νν

1 60 5 (4.3)

The energy balance over the char layer consists of two heat sources; heat from thereaction front, qr, and heat from the char combustion, qc.

1− ∂∂

= + + −ν ρ δ0 5 c pcc c r

cs c radc

T

t

q q

xx x x (4.4)

T is temperature, ρ density, cp heat. In the initial stage when the layer downstreamthe reaction front, surface plus char layer xs+xc, is thinner than the penetration depthof the radiation from above the bed into the bed, xrad, no char layer is defined. Thisinitial stage is modelled by a Heaviside step function δ. The energy balance over thesurface of the bed consists of: radiation from the surrounding, q0,rad, char combustion,qs, heat convection from the gas, qsg, and in the initial stage, when the char layer isnot developed, heat from the reaction front, qr.

10− ∂

∂=

+ + + − +ν ρ

δ0 5 1 6

s pss rad s sg r rad s c

s

cT

t

q q q q x x x

x, (4.5)


4.1.1 Reaction front

The temperature in the reaction layer is in the model defined by the temperature inthe char layer and therefore is the heat produced or consumed in the thin reactionfront in he reaction front is immediately transported to the char layer. The gas and thechar are assumed to leave the reaction front at the temperature of the char layer (inthe beginning when the layer downstream the reaction front is thinner than thepenetration depth, of the radiation this temperature is equal to the surfacetemperature). The mass release per unit area in the reaction front is equal to the heatflux per unit area to the unreacted fuel layer, qUeff, divided by the heat per unit massneeded for heating up the fuel to the devolatilization temperature and to evaporatethe moisture, QU:

∂∂

=m

t

q

Qr Ueff

U

(4.6)

The reaction front can be divided into four zones see Figure 4.2. The first zone iswhere the surface of the particles is heated up to the evaporation temperature. Heatis transported to the particle surfaces in this zone by radiation and conduction fromthe warmer zones downstream and heat is transported away from the particlesurfaces by convection to the gas. The convective heat transfer coefficient is highand the gas temperature rises to approximately the same temperature as that of theparticle surface. The second zone is dominated by drying. In this zone the gas flowout from the particle reduces the influence of the convective flow and the radiativeand the conductive heat flow transfer the heat. The third zone is defined by thedevolatilization. Dependent on particle size, there will be a period of simultaneousdrying and devolatilization. In this case the gas flow out from the particles is high andthe convective heat transfer is small like in the second zone. In this third zone ignitionof the gas takes place and the gas temperature rises fast. If there is asubstoichiometric condition in the reaction front, the temperature of the gas becomeshigher than that of the char layer. The radiative heat flux of the gas can increase theheat flux to the particle surfaces in all zones, and the surface temperature of theparticles can reach a higher temperature than the temperature in the char layer. Thefourth zone is at the very end of devolatilization. In this zone the gas flow from theparticles is low, and if there is oxygen left, char combustion will start. The convectionis once more important, and the temperature of the gas and the particles converge tothe same temperature.


zone 1 zone 2 zone 3 zone 4

Length along reaction front

Mas

slo

ss

WaterVolatiles

Figure 4.2. The mass loss of moisture and volatiles in the reaction front. The figure isreproduced from figure of Saastamoinen [1998]

The maximum radiative and conductive heat flux which evaporates moisture anddevolatilizes the particles is proportional to the difference between the highesttemperature in the reaction front, Tr, and the temperature in the unreacted fuel layer,TFs, minus the heat needed to heat up the primary gas, qUg, to the evaporationtemperature, Tdry . The true heat flow for evaporation and devolatilization is smaller. Itis assumed to be equal to the maximum heat flux reduced by a coefficient k. Themodel does not calculate the temperature profile of the gas and the solid in thereaction front and the maximum heat flux is not calculated. The heat flux is thereforerelated to the radiative heat flux between the char layer and the unreacted fuel layer,and a fitting coefficient k1 is introduced.

q k T Tx

T T q k T T qU r Fseff

r Fs Ug c Fs Ug= − + −

− = − −εσ

λεσmax max1 64 9 1 62 7 2 74 4

14 4

∆(4.7)

ε is emissivity, σ Stefan-Bolzmann’s constant, λ heat conductivity and ∆x is thedistance between the position of the highest temperature in the reaction front and theunreacted fuel layer. The reaction front can only go in one direction and therefore hasthe heat flux be restricted to a positive value.

qq q

qU

U U

U

=>≤

%&'

0

0 0(4.8)

Due to the low heat capacity of the gas and the high convective heat transfercoefficient in the bed the gas attains the same temperature as the fuel, and the heatneeded to heat up the gas from this temperature to evaporation temperature is

q J I T I TUg i i dry i Fsi

= −∑ 4 9 (4.9)


J is molar flow per unit surface area, I enthalpy, subscript i indicates the differentspecies, and dry stands for drying.. The mass release per unit area given byEquation (4.6) assumes heat transfer control of devolatilization, but if the temperaturedecreases the devolatilization will be controlled by kinetics. It is also assumed thatthere exists a heat source by the oxidation of the volatiles leaving the particles. So,there is only a reaction front if the temperature is high enough for devolatilization. Anempirical function is therefore introduced to describe the transition between kineticand heat transfer controlled devolatilization. When the devolatilization is controlled bykinetics, the rate is low and fr →0, but when it is controlled by heat transfer fr→1. Theempirical function is based on the kinetics of devolatilization:

f TE RT

k E RTr cc

c

=−

+ −exp /

exp /

1 61 62

(4.10)

E is activation energy, R gas constant and k2 is an empirical constant whichdetermines the position of the temperature range of devolatilization. At hightemperatures internal heat transfer in the bed particles controls the mass release.The maximum internal heat transfer can be calculated using the Biot module, Bi. Bylimiting the maximum heat flow for the drying and devolatilization, qmax, the fittingconstant k1 in Equation (4.7) can be optimised for the temperature range between theextremes. The effective heat flux for drying and devolatilization is restricted by theheat flux from Equation (4.7)

qq f T q f T q Bi

q Bi q f T q BiUeffU r c U r c U

U U r c U

=<≥

%&'

;

;max

max max

(4.11)

The limiting maximum heat flow is at present adjusted as a fitting coefficient. Theheat per unit mass needed to evaporate the moisture and to heat up the fuel to thedevolatilization temperature is

Q Y I T I T M

Y I T I T M

Y I T I T M

Y I T I T M

U H O H O g dry H O l Us H O

vol vol s vol vol s Us vol s

char char vol char Us char

ash ash vol ash Us ash

= − +

− +

− +

−

2 2 2 2( ) ( )

( ) ( ) ( )

/

/

/

/

4 9

2 72 72 7

(4.12)

Y is mass fraction of fuel, M molar mass and subscript vol stands for volatiles. Theestimation of the composition and enthalpy of the volatiles are presented in AppendixA. In the reaction front the solid and the gas leaving the particles are heated upfurther to the temperature of the char layer. The heat per unit mass needed is:


Q Y I T I T M

Y I T I T M

Y I T I T M

Y I T I T M

r H O H O g c H O g dry H O

vol vol g c vol s vol vol g

char char c char vol char

ash ash c ash vol ash

= − +

− +

− +

−

2 2 2 2( ) ( )

( ) ( ) ( )

/

/

/

/

4 9

2 7

2 72 7

(4.13)

The assumption that no heat transfer takes place in the unreacted layer gives theenergy needed to rise the temperature of the primary air to the temperature of thechar layer:

q J I T I Trg i i c i Ugi

= −∑ 4 9 (4.14)

The major heat source in the reaction front is oxidation of hydrocarbons and carbonmonoxide. The entire set of reactions of the major species in the bed is modeled asfollows:

CH m O CO H O

CO O CO

mm+ + ⇒ +

+ ⇒

12 2 2 2

12 2 2

1 4

4

0 5 .

.

I

II

m is the number of hydrogen atoms per carbon atom in the hydrocarbons. It isassumed that the local mixing controls the reaction rate according to the concept ofMagnussen and Hjertager (1977), which states that the reaction rate is controlled bythe minimum concentration of oxidant, reactant or product. Reactions that producethe products, carbon dioxide and water, are already ongoing during thedevolatilization process, and the products never restrict the reaction rate. Thereaction rate is therefore controlled by the minimum concentration of oxygen or fuel.The gas leaving the particles changes in the reaction front, both in quantity and incomposition, from water rich to volatile rich. To simplify the descriptions of gas flowand composition in the reaction layer, the quantity and the composition of the gasleaving the particles are assumed to be constant along the entire reaction front. TheMagnussen and Hjertager concept is described by the mixing rate, b, and theminimum of the oxygen or the fuel. The mixing rate is assumed to be proportional tothe turbulent kinetic energy divided by the dissipation of turbulence. Inside the bedthe flow can not be turbulent due to the narrow channels between the particles. Thelocal mixing is therefore not created by the turbulence but of the impulse force of thegas flowing out from the particles. For this reason the local mixing rate is assumed tobe proportional to the gas flow out from the particles.

b jk= 3 (4.15)

j is gas flow per unit time from the particles and k3 is a coefficient to be determined.The total molar flow out from the particles, jtr, tr is the residence for the gas in thereaction front is given by the mass loss in the reaction front per unit area.


jtm

tY M Y Mr

rvap H O vol vol g= ∂

∂+/ / ( )2

3 8 (4.16)

The residence time in the reaction front can be estimated by assuming the width ofthe reaction front xr, where the J0+1/2jtr is the mean molar flow in the reaction front.

tx

J jt

P

RTrr

r

=+

ν0

12

(4.17)

The change of the molar flow of oxygen, JO2, and fuel, JCH4, JCO, is the differencebetween the total molar flow out from the particles and what is consumed byreactions.

∂∂ ′

= −+ ′

∂∂ ′

= −+ ′

−

∂∂ ′

= −+ ′

+ +

J

tjX

b

J jtJ J

J

tjX

b

J jtJ J J J

J

t

b

J jtm J J J J

CHCH CH O

COCO CO O CH O

OCH O CO O

m

m m

m

m

0

0

0

12

12

2

2 2

2

2 21

min( , )

min( , ) min( , )

min( , ) min( , )

3 8

0 53 8

(4.18)

t´ is the local residence time in the reaction front, t’=0 when the primary air enters thereaction front and t’=tr when the gas leaves the reaction front, J0+jt’ is the total molarflow at time t’ and X is molar fraction. An analytical solution of the system ofdifferential equations, Equation (4.18) is favourable in order to speed up thecalculation. Such a solution can be found under the following conditions,

J J J J

J J J J

J J J J

CH O CO O

CH O CO O

CH O CO O

n

n

n

≤ ≤

> ≤

> >

2 2

2 2

2 2

3 8 3 84 9

3 8 3 84 9

3 8 3 84 9

&

&

&

(4.19)

These conditions are fulfilled in all situations of interest for combustion of volatilegases from wood. The only case when condition (4.19) is not fulfilled is when thefraction of carbon monoxide in the volatile gases is not much smaller than the fractionof hydrocarbons. The analytical solution is presented in Appendix B. The productionof reaction products is:

∆

∆ ∆

J J X jt J t

J J J X jt J t

H Om

CH CH r CH r

CO m H O CO CO r CO r

m m m2

2 2

2

2

0

0

= + −

= + + −

3 8(4.20)

The energy release of reaction is:

q J I TR i i ci

= ∑∆ (4.21)


Subscript R stands for reaction. The heat flux from the reaction layer to the char layeris then obtained from the Equations (4.6),(4.12), (4.13), (4.14) and (4.21)

q q q Q Qm

tr R rg U r

r= − − + ∂∂

1 6 (4.22)

4.1.2 Char and surface layer

During the drying, devolatilization and char combustion, the size of the particlechanges; wood chips shrink by volume with 10 to 20% of the initial fuel size duringdrying, with 40 to 60% of the dry fuel during devolatilization and with 95 to 99% of thedevolatilized fuel during char combustion. The shrinkage factors of drying, Sdry,devolatilization, Sdev, and char combustion, Schar, describe the shrinkage. They aredefined

S V V

S V V

S V V

dry dry

dev dev dry

char ash dev

= −

= −

= −

1

1

1

0/

/

/

2 7

2 71 6

(4.23)

Vdry is the volume of the dry fuel, Vdev volume of devolatilized fuel and Vash volume ofash-For spherical particles with the same shrinkage in all directions, the char particlediameter is a function of the moles of char divided by the initial moles of char Xc.

d d S S S Xdry dev char c= − − − −0

1 3

1 1 1 12 71 6 1 62 74 9/

(4.24)

The thickness of the surface layer, xs, is the minimum of the penetration depth of theradiation coming from downstream the bed surface, xrad, and the thickness of the bedlayer downstream the reaction front, xs+xc:

x x x xs rad s c= +min ,1 6 (4.25)

The thickness of the bed layer downstream the reaction front is:

x x x x S S S X dxs c b U dry dev char char

x

x

U

b

+ = − − − − −I1 62 71 6 1 62 71 1 1 1 (4.26)

Equations (4.4) and (4.5) re not defined initially when xs and/or xc are equal to zero.Therefore it is necessary to limit these quantities in the calculation to a small value.

The penetration depth of the radiation flux, qrad, is defined as the length xrad where95% of the radiation is attenuated,


q

q ldxrad

rad m

xrad

0 0

11 0 95

,

exp .= −

= −I 0 5 (4.27)

q0,rad is the radiation fluxes incident on the bed surface, x=0, from above and lm is themean path-length of radiation. The mean path of radiation is defined as

ln Am

p p

= 1(4.28)

np is the number of particles per unit volume and Ap is the mean projected area of theparticles. For spheres with the diameter d, the mean path-length is, Hernberg et al.[1993]:

ld

m =−

2

3 1 ν(4.29)

Downstream of the reaction front the char combustion starts. The char combustion ismodelled by a single reaction:

C nO n CO n CO+ ⇒ − + −2 22 2 2 10 5 0 5 4.III

n are the moles of oxygen consumed for one mole of carbon. If the reaction iscontrolled by the diffusion of oxygen to the particle, the reaction rate becomes,

∂∂

= ∂∂

∂∂

=∂∂

= −C

t

x

t

C

xu

C

xC A x x

O Og

OO eff s U

2 2 2

2β δ (4.30)

C is concentration, β mass transfer coefficient to the external surface of the particle,As specific surface area of bed particles, ug gas velocity. The step function restrictsthe char combustion to downstream of the reaction front. Since the char combustionis assumed to be diffusion controlled, the model can not describe the extinction of thechar combustion at a high flow of primary air. The introduction of a reaction rate forthe char combustion does not solve this problem, because the temperature in thereaction front is not modelled. Setting a limiting temperature for the char combustioncan make the error smaller. The effective mass transfer coefficient, βeff, is theexternal mass transfer coefficient including also mass transfer trough the ash layerbuilt up on the particle surface during char combustion,

β β ββ

βeff O O O surO eff

ashO sur eff

D

x

D

x

C C CD

xC

O eff

ash

O eff

ash

2 2 2

2

2

2

20= − = − ⇒ =

+, ,3 8 3 8∆∆

∆

(4.31)

DO2,eff is the effective diffusivity in the ash layer. Because the porosity in the ash layeris close to unity, the effective diffusivity is about the same as the diffusivity of the gas.The thickness of the ash layer ∆xash is:


∆x d d S S Xash dry dev c= − − −

12 0

1 3

1 12 71 64 9/

(4.32)

The Nusselt number, Nu, for the channels between the particles inside the with ahydraulic diameter, dh, and a channel length l becomes

NuPeldh

=

1615

13

. (4.33)

The Peclet number, Pe, is

Peu d cg g h pg

g

=ρ

λ(4.34)

and the hydraulic diameter and channel length is

d dh =−

2

3 1

νν

(4.35)

l d= π2

(4.36)

The mass transfer coefficient is calculated by assuming that Nusselt´s number isequal to Sherwood´s number,

Nu Shd

D

D c u

dh

O

O pg g g

g

= = ⇒ =−

β βρ ν

πλ ν2

23 13

2

1 30 5 /

(4.37)

The specific surface area of bed particles is:

Ad

d

dsc= −

6 1 2ν ν0 5(4.38)

dc is the char core diameter.

d d S S Xc dry dev c= − −0

1 3

1 12 71 64 9/

(4.39)

The gas velocity in each bed layer is given by the molar flow of each species:

uRT J

Pg

ii=

∑ν

(4.40)

P is pressure. By dividing the bed layer into z sub-layers and assuming that gasvelocity, mass transfer coefficient and specific area are constant in each layer,Equation (4.30) can solved for a height element ∆xi,


C CA

ux f iO i O i

eff i si

gii2 2 1 1, , exp= −

−

β∆ (4.41)

f1[i] is the step function, δ, integrated over the element ∆xi. f1=0 if the element islocated upstream of the reaction front and f1=1 if the element is located downstreamthe reaction front, see Figure 3.

f1,

δ

1

0

∆x1 ∆x2 ∆x3 ∆x4 ∆x5 ∆x6

Reaction front

Figure 4.3 delta function integrated over element ∆xi

If the reaction front is inside the element, f1 gives the relative position of the reactionfront in the element. The position of the element i is given by the summation of theelements j=1 to j=i, where i≤z, this can be expressed

f i

x x

x x x x x x

x x

j Uj

i

jj

i

U i j Uj

i

jj

i

U jj

i

1

1

1 1

1

1

1

1

0

1

=

<

−

≤ ≤

<

%

&

KKK

'

KKK

=

= =

−

=

=

−

∑

∑ ∑ ∑

∑

∆

∆ ∆ ∆ ∆

∆

/ (4.42)

The thickness of the active char layer elements ∆xi is

f i

xx

zf i S f i S S X f i f i

f i

x

ib

dry vol char char i

i

1

1 1 1 1

1

0

1 1 1 1 1

0

0

>

= − − − − − −

==

∆

∆

2 71 6 1 62 73 84 9, /(4.43)


The consumption of oxygen in the active char layer element is:

∆ ∆J JA

uxO i O i

i si

gii2 2 1 1, , exp= −

−

−

β(4.44)

and of char:

∂∂

=

∂∂

=

n

t nJ

X

t n

J

n

C iO i

char i O i

C i

,,

, ,

,

1

1

2

2

0

∆

∆(4.45)

The initial moles of char in the active char layer element is:

nx

z

Y

Mf iC i

b char F

char, 0 1

1= −ρ ν0 5

(4.46)

The bed temperature in the sublayer Ti is the same as for the char layer when x issmaller than xs and Ts when x is larger than xs. For the bed sub-layer that includesthe border between the char and the surface layers an integrated mean temperatureis used,

T T f i T f ii c c= + −2 211 6 (4.47)

f2 is a step function integrated over an element in the same way as Equation (4.42) ,with the difference that f2 is 1 below the surface layer and 0 above.

f i

x x

x x x x x x

x x

j sj

i

jj

i

s i j sj

i

jj

i

s jj

i

2

1

1 1

1

1

1

1

1

1

0

=

<

−

−

≤ ≤

<

%

&

KKK

'

KKK

=

= =

−

=

=

−

∑

∑ ∑ ∑

∑

∆

∆ ∆ ∆ ∆

∆

/ (4.48)

The heat release during the char combustion is:

qn

tI T nI T n I T n I Ti

C iC i O i CO i CO i=

∂∂

− − − − −,

2 22 2 2 10 5 0 53 8 (4.49)

The heat release in the char and the surface layers is:


q q f i

q q f i

c ii

z

s ii

z

=

= −

=

=

∑

∑

21

21

11 6(4.50)

The heat corresponding to the temperature change of the gas between the char layerand the surface layer is:

q J I T I Tsg i i s i ci

= −∑ 2 7 (4.51)

The density and heat capacity of the fuel in the char and in the surface layer are:

ρρ ρ

νic i char char ash ash

c i char ash

X Y Y

X Y Y=

++

−,

,

10 5 (4.52)

cX Y c T Y c T

X Y Ypichar i char pchar i ash pash i

char i char ash

=++

,

,

(4.53)

Subscript i indicates the char and the surface layer.

4.1.3 Packing of bed

The packing of the bed changes with time. For wood chips the bed voidage is highestin the beginning and decreases during the combustion process. A major reason for achange in the bed voidage is a change of velocity of the bed along the grate. Whilethe velocity of the bed decrease along the grate and the pressure forces inside thebed is built up. These pressure forces decrease the bed voidage and increase theheight of the bed according to the continuity equation. If it is assumed that the bedvoidage is proportional to the change in velocity of the bed along the grate, and theinitial and minimum bed voidage are known, the bed voidage at a certain position onthe grate becomes:

vu u

u ub b

b b

= + −−−

ν ν νmin minmin

min0

0

1 6 1 61 6

(4.54)

ubmin is lowest velocity of the bed along the grate, and the minimum bed voidage isreached at this velocity.

4.2 Description on free-room calculation and CFD Software used

The software used for the calculations of the free-room is Fluent/UNS 4.2.5. Thissoftware package has built in the necessary physical models to simulate gas phasecombustion (turbulent fluid flow, chemical species mixing and reaction, conductive,convective and radiant heat transfer). The package includes software for domaindefinition and discretization, and may be integrated with a nitrogen oxide reactionmodule. It also contains some bugs, which will be discussed later in this report.


The software uses a finite volume discretization scheme for solving the equationsthat define the problem. The equations are:

• The continuity equation,• The Navier-Stokes time averaged equations,• The transport equations for the various chemical species,• The transport equations for turbulent variables (k and ε).• The discretization transforms each partial differential equation in a set of linearequations (one for each cell), which is solved not inverting the set but using aniterative tool called “Algebraic Multigrid Linear Equation Solver”.

The steps in the problem set-up and solution procedure are the following:

• definition of the geometry of the volume (domain) where the equations will besolved,

• discretization of the domain in a number of control volumes (cells),• choice of the physical models to be applied,• definition of the boundary conditions,• choice of the numerical methods and parameters,• iteration,• refinement (adaption) of the cells structure (grid) in the critical areas,• iteration,• post processing,• solution analysis.

4.2.1 Numerical scheme

To illustrate the discretization of an equation a simple one-dimensional diffusionequation is used. The differential equation is written:

∂∂

ρ φ∂∂

∂φ∂ φx

ux x

S( ) = +Γ (4.55)

After integration over a control volume (cell) and discretization the equation is writtenas:

J Jx x

A S Ve e w w eE P

ew

P W

w

φ φφ φ φ φ

φ− =−

−−

+( )Γ∆

Γ∆

∆ (4.56)

Where φE, φP and φW are the values of the variable in the centroids of the cells, φe andφw are the values on the surfaces of the cell, Je is the mass flow through surface e, Ais the cross-sectional area, and ∆V is the volume of the cell, Sφ is a source term and∆x is the distance between two cells, as shown in Figure 4.4.


∆xw ∆xe

W P E

w e

Figure 4.4 One-dimensional discretization of equation

The UNS code stores the value of the variables at centroids, and interpolates thesurface values. The interpolation can be performed in three ways:• assigning to the variable φ on the surface the value of in the upstream cell (first

order upwind discretization scheme)• computing the value as a second order Taylor expansion from the centroid of the

upstream cell. The value of the gradient is computed satisfying the divergencetheorem. (second order upwind discretization scheme)

• solving the Peclet equation, which is an interpolation between the cell’s centroidsbased on the features of the flow. It assigns to the surface the value of theupstream cell centroid if the flow is dominated by convection, it computes a linearinterpolation if the flow is dominated by diffusion and uses an intermediate valueotherwise (power law discretization scheme).

The choice of the discretization scheme affects the solution in terms of the precisionobtained, but it also affects the convergence speed of the iterative process.When it is possible, it is suggested to use the second order discretization scheme.For non-reacting flows the second order discretization scheme may be appliedsuccessfully, but in the present case, though, when fast chemical reactions such ascombustion are included in the flow, the algorithm is not stable enough to converge,not even slowly. Even with the first order discretization scheme, reacting flows causeconvergence problems, but they can be overcome using a stronger underrlaxationthan the default. The pressure-velocity-coupling algorithm is the one suggested fortransient flows (SIMPLEC). The equations are solved separately, beginning from themomentum equations, following with the continuity equation, and then the otherscalar equations. The convergence criteria used are the default ones of the code,which are quite strict. The criteria are satisfied when the normalised residual for avariable has decreased to a fixed percentage of the initial normalised residual. Thenormalised residual of a variable is defined as the sum over the entire domain of themodulus of the residuals of the linearized equation, divided by the total flow of thevariable through the domain.

The computer used has a Sun Ultra processor and 500MB of RAM memory, and ittakes approximately 7 min to perform one iteration in the complete case (about300000 cells, 12 independent variables, and the radiation model).

4.2.2 Domain discretization

The discretization of the domain is performed using the P-Cube software, trying toachieve “grid independence”, which is accomplished when a further refinement of the


grid does not cause any significant change in the solution. The grid used is thehexahedral one, since the geometry of the boiler can be easily represented as a setof rectangular prisms and pyramids. Section of the grid is shown in Figure 4.5.

Figure 4.5 Section of grid

An excessive refinement of the grid must be avoided in order to limit the computationtime. The correct approach is therefore to refine the grid only in the areas wherestrong gradients of important variables are present (adaption). The gradients thatthat controls the reacting flow are the ones of velocity and of oxygen concentration,those have very high values on jets and on reaction fronts. By refining the grid in thevolumes occupied by the jets, a more accurate description of the velocity fieldincreases the penetration of the jet and improves the description of the flow aroundthem. A typical procedure to obtain grid independence is to refine the grid in the jetarea until the penetration of the jet does not change with a further refinement.Refining the grid in the reaction front area could increase significantly the quality ofthe description of combustion where NOx reactions take place, therefore improvingthe estimation of the NOx production. Adaption of the grid is also useful to obtain agrid that matches the size of the boundary layer, for reasons discussed further on.The adaption tool unfortunately doesn’t work in simulations where the DiscreteTransfer Radiation Model is used, due to a bug described in paragraph 4.2.4.2. Othercriteria to be observed in the production of the grid are the alignment of the grid tothe flow and the minimisation of cells skewness. Alignment of the grid to the flow canbe obtained only where the flow field has a simple and obvious direction, i.e. wherethe air and gas jets are located. Extreme cell skewness can be avoided if thegeometry is not too complex, otherwise it may be better to use a tetrahedral mesh.


4.2.4 Physical models for fluid flow

The program solves the momentum equations and the continuity equation for timeaveraged variables. The Reynolds stress tensor is considered proportional to thelaminar stress tensor through a multiplying factor, which is a function of turbulentkinetic energy and its dissipation rate. Two more balance equations are solved forthe turbulent kinetic energy k and its dissipation rate ε, the so-called k-ε closure of theturbulent problem. At the wall boundaries, the set of equations is not valid, becausethe hypothesis of homogeneity and anisotropy of the turbulence, which is at the basisof the model, is no longer valid. Therefore, empirical functions are used to describethe variables in the cells adjacent to the wall. In the present case the description ofthe flow in the vicinity of the walls is a matter of secondary importance, since themost important mechanism of heat transfer is radiation, due to the high temperaturedifference between the flame and the tube walls, and the production of k and ε at thewalls is negligible compared to the production in the secondary air and therecirculation jets. For this reason the computational resources are not used to obtaina correct representation of the boundary layer. The code offers three options formodelling the flow near walls, the “Standard Wall Function”, the “Non EquilibriumWall Function” and the “Two Layers Zonal Model”. The first two are functions thatdescribe the profile of the variables on an empirical basis instead of solving a set ofequations, the third option is a model that solves a modified set of equations insidethe boundary layer. This last model requires many cell layers inside the near wallarea and has to be excluded because of the large computation time requirements.The “Non Equilibrium Wall Function” is a model intended for flows with strongpressure gradients, which is not the case in the boiler studied. Therefore the simpler“Standard Wall Function” is employed. This approach assumes that the production ofturbulent kinetic energy is equal to its dissipation rate (local equilibrium hypothesis).The transport equation for k is solved, while ε is computed using an empiricalfunction. The velocity function is linear in the viscous sublayer (y*<11) andlogarithmic outside (y*>11). The velocity function is valid in the boundary layer(y*<60), but it is applied to the whole adjacent-wall cell, so if this cell is larger than thelayer, an error is introduced in the calculation of the velocity in this cell. Producing agrid that satisfies this condition on all walls is possible only for simple flows such asone in a duct, but it is practically impossible in a complex flow like the one in thefurnace analysed. The size of the cells that would fit in the boundary layer is muchsmaller these of the rest of the domain, and to represent the boundary layer it wouldbe necessary to decrease the size of the cells at the walls. Since the boundary layeris considered to be of secondary importance, this requirement is not fulfilled,therefore introducing an error. The error involves not only the velocity in the wall-adjacent cell, but also the temperature, since also the temperature field is not solvedbut determined by an empirical function. The temperature may be underestimated (ifthe cell is larger than the boundary layer) because in the laminar sublayer and in thetransition zone the heat transfer is lower than in the turbulent region. However, thethermal boundary layer thickness is in general different from the velocity boundarylayer, so the error would exist even if the grid was built with a thickness of y*=60. Toverify whether the error affects significantly the solution, a pair of two-dimensionalcase was studied where all conditions are identical with the exception of the grid inthe vicinity of the walls. In one case the dimension of the cells is such that thecondition 30<y*<60 is satisfied almost everywhere, while in the other case these cells


have a dimension similar to that of the neighbouring cells, which is much larger. Theresults from the two cases show that the difference between the heat powerstransmitted to the walls is negligible, confirming that the main heat transfermechanism is radiation, and that the thickness of the cell layer does not affect theheat power significantly. All the fields were compared in a qualitative way, withparticular attention to the velocities and turbulent quantities, and no importantdifferences appear. For the final tri-dimensional case it was therefore decided not torefine the grid near the walls.

The boundary conditions are set as follows:

• the secondary air and recirculation gas inlets are defined as surfaces withconstant velocity over the area.

• the turbulent energy and the dissipation rate of the jets entering the combustionchamber are computed using the formulas available in the Fluent manual forflows in a duct.

• the outlet is defined as a surface at the constant pressure of 1 bar (the rest of theboiler has a slightly higher pressure).

• on the upper surface of the bed (the inlet to the combustion chamber) the velocityis a function of the distance from the fuel inlet. (The function is an output of thebed model)

• the turbulence exiting the bed is quite difficult to estimate, but it is reasonable tosay that the fuel layer has an effect similar to a porous medium. Therefore theflow should have the characteristics of weak grid turbulence. The importance ofthis boundary condition, however, is limited, since the turbulence of therecirculation jets reaches the upper surface of the bed, so that the contributionfrom the bed itself would be negligible.

• at the walls the boundary condition is set by the wall function.

4.2.5 Physical models for heat transfer

The conservation of energy is satisfied solving the thermal energy equation:

∂∂

ρ∂

∂ρ

∂∂

∂∂

∂∂

τ∂∂t

hx

u hx

k kT

x xh J

Dp

Dt

u

xS

ii

it

i ij i j ik eff

i

kh( ) ( ) ( ) ( )+ = + − + + + (4.57)

Where h is the specific enthalpy and the terms on the right hand side of the equationrepresent:

• conduction (kt is the conductivity due to turbulence)• enthalpy transfer due to diffusion of species (Jij is the diffusive flux of species j in

direction i)• the reversible work• irreversible dissipation of kinetic energy due to friction (probably negligible if

compared to the turbulent dissipation rate)• a source term that contains the effect of radiation.


The Fluent/UNS code includes two options to model radiation, which are calledDiscrete Transfer Radiation Model (DTRM) and P1 model. Both models use aweighted sum of grey gases to determine the emissivity of a layer of fluid as afunction of the concentrations of CO2 and H2O and of the thickness of the layer. Thisfunction is a polynomial of temperature fitted to experimental values. The contributionof soot to the emissivity of the fluid cannot be included in Fluent/UNS. The role ofsoot in radiation is quite important and the neglecting of soot may produce anunderestimation of the radiant power transmitted to the bed.

Figure 4.6 Rays and clusters, as used in the DTRM mosel.

The DTRM describes the radiation exiting from a surface as a finite set of rays thattransport the energy to the cells that they cross, see. Figure 4.6. The variation ofpower along a ray is expressed by the following equation:

∂∂

σπ

I

saI

a T+ =

4

(4.58)

where I is the power flowing along the ray, a is the absorption coefficient per unitlength of the fluid and σ is the Stefan- Boltzmann constant. The volume discretizationof the DTRM is coarser than the discretization for the solution of the other equations.One single DTRM cell (called a cluster) is actually a group of 30 cells of the grid. Theclusters are defined before the iterative process starts, together with the rays. Aproblem that arises during the preparation of the rays and clusters is the lack of aninstrument capable of evaluating the effectiveness of the representation. For exampleit is not possible to verify whether each cluster is actually crossed by at least one ray,and therefore whether it can actually exchange radiant heat with the neighbouringcells. Furthermore, when defining the rays (ray tracing phase) a bug appears. Thisbug causes the rays to cross the boundaries of the domain, ending in a not definedspace. This error is limited to a few rays in the case of a “basic grid” but increaseshighly for “adapted grids”. The result is that the DTRM cannot be used on refinedgrids. This problem strongly limits the usefulness the code, because it should bepossible to perform the grid adaption in order to obtain a solution that has a sufficient


precision. An effort was made to produce a structured grid already refined in thecritical areas, but the skewness increased, drastically slowing down the convergence.

In the P1 model the radiant heat transfer is expressed by the following balanceequation of incident radiation:

∇ − + =( )Γ∇G aG a T4 04σ (4.59)

where G is the incident radiation flux and Γ is a function of the absorption coefficient.The equation has the shape of a diffusion equation and therefore this kind of modelworks well for optically thick media, where radiation travels small distances. In thecase treated the optical thickness of the medium is small, but it is interesting to applythe model anyway, since the DTRM does not work properly. However, the result isnot satisfactory because the algorithm needs a very high number of iterations toreach convergence. For this reason it is not practical to use this model for tri-dimensional cases. Using the P1 model some information can be obtained on theeffect of grid adaption. The main difference that appears when adapting the grid inthe jet zones is a slight increase of the penetration of the jet. Adaption on the reactionfront was not performed.

The boundary conditions are set as follows:

• Temperature of the refractory walls: 900K• Temperature of the tube walls: 500K• Emissivity of all walls: 0.7 (using this value, the computed heat power transmitted

to the walls equals the measured one)• Emissivity of the bed: 0.9• Emissivity of the other boundaries: 1

Reflection and emission are considered to be diffuse for all surfaces, the values oftemperatures are taken from measurements in another plant, and the variation oftemperature along the tubes, due to heating of the water is neglected. Anyway thelower temperature plays a minor role in the determination of the radiant flux, since itdepends on temperature to the power of four.

4.2.6 Physical models for reaction kinetics

In the studied case the reactants enter the combustion chamber separately, so that amixing is required before the reaction can take place. The mixing rate can be thelimiting factor of the combustion process, and therefore it is necessary to estimatethis rate in the various cells. To perform this estimation, the code uses a model builton the Eddy Dissipation Theory of Magnussen and Hiertager [1989]. This modelassumes that the last step of the turbulent energy cascade (the dissipation of kineticto thermal energy) takes place in fine structures where the mixing occurs at amolecular scale, making it possible for the various species to react. The quantity offuel that may react per unit time is therefore a function of the flow of reactants thatenters the fine structures. The model of Magnussen and Hjertager produces twoexpressions for the generic reaction B+C->D+F :


[ ] [ ]r B const B Ck

( ) ( )= +1

ε (4.60)

[ ] [ ]r B const D Fk

( ) ( )= +2

ε(4.61)

These expressions are compared to the Arrhenius rate:

[ ] [ ] [ ] [ ]r B A B C D FE

RT( ) exp( )= −β β γ δ ϕ1 1 1 1 (4.62)

and the lower (limiting) one of the three is used by the code. The resultingproduction or consumption of chemical species is introduced in the transportequations of the various species as a source term. In cases where the chemicalkinetics are very fast, it is not necessary to calculate the value of the Arrheniusexpression, and some computational resources may be spared. In the present case,though, both the reaction rates of CO and CH4 are not fast enough. The secondexpression, which appears contradictory at a first look, is derived from aconsideration that may be briefly summarised saying that the absence of products ofreaction implies that a reaction has not occurred recently. Therefore radicals whichare necessary for the activation of further reaction are not available. The conceptcannot be applied to calculations were products of reaction are provided by othersources. In the present case for example, the products of reaction (H2O and CO2)are present in high concentrations already in the combustion air and in therecirculated flue gas entering the chamber, so the expression always assumes highvalues, preventing it from being the limiting factor. It may also be argued that suchexpression has a value of zero where there are no products of reaction, and hinderscombustion even if there are reactants at a high temperature. In the numericalmethod anyway the residuals always provide a minimum presence of reactants, thatproduce the numerical “ignition” of the flow. Then the radical diffusion is modelledtogether with that of the reactants.

4.2.5 Simplified combustion schemes

In the processes of combustion and pyrolysis is involved a large number of chemicalspecies that interact in a complex system of reactions. Therefore it is not possible todescribe the complete mechanism in a fluid dynamic simulation of a complex flowand simplified combustion schemes are used which include a limited number ofspecies and reactions. The main chemistry has been modelled by two differentreaction schemes, and the results were compared. The first scheme is the oneavailable in the database of the Fluent code for methane combustion. It includes thefollowing reactions:

CH4+3/2O2->CO+2H2O 4.IVCO+½O2->CO2 4.V

In the database the carbon dioxide dissociation reaction was also included, but therate of dissociation is negligible at the temperatures present in the furnace. Hydrogen


is not included because this pyrolysis gas is not measured in the boiler, furthermore itis not very relevant to any of the reactions involving nitrogen compounds (in fact, itsconcentration does not appear in the reaction rate expressions). The second reactionscheme for the main chemistry is the one formulated by Jones and Lindstedt [1988]for methane combustion. It includes the following reactions:

CH4+1/2O2->CO+2H2 4.VICH4+H2O->CO+3H2 4.VIIH2+1/2O2->H2O 4.VIIICO+H2O->CO2+H2 4.IX

In this case hydrogen obviously plays an important role, being the product of bothmethane and carbon monoxide partial oxidation, so it has to be included. Thisreaction scheme, however, proved to be inadequate to the conditions existing in thisboiler, i.e. very high moisture content at all stages of combustion (the fuel has a veryhigh water content and the combustion air is moisturised). Using this scheme causesall the methane and the carbon monoxide to be split by the water just above thegrate, producing a high hydrogen concentration and a complete absence of othercombustible gases in the combustion chamber. This clearly contradicts themeasurements that instead show the presence of both carbon monoxide andhydrocarbons below the secondary air injection.

Both combustion schemes lack the soot formation reaction. The inclusion of sootmodelling in the combustion simulation would probably modify significantly thesolution for two reasons. First the presence of soot increases the emissivity (andabsorption coefficient) of the gases, making the flame more luminous and thereforeincreasing the radiant heat transfer, second it affects the rate of oxidation of thecarbon (the soot oxidation is different from that of CO or CH4), displacing the flame toanother position in the furnace.

5. The NOx modelling

Like the modelling of the main chemistry, the NOx modelling is calculated separatelyfor the fuel layer and for the free-room, where the fuel layer also in this case acts asa boundary condition for the free-room. The NOx add-in model available from Fluentdescribes the NOx processes in the free-room. This model is developed for coalcombustion, and HCN is used as a NOx precursor and not NH3, which would be moreappropriate for biofuel. On the other hand the add-in model includes well knownreaction rates for formation of thermal NOx and for the formation or destruction ofNOx by NH3. In the present case NH3 is assumed to be formed instantaneously fromthe HCN. A reduced mechanism developed for biofuel would be preferred, but theimplementation and validation of such a model element into Fluent is too large a workfor this project. The nitrogen chemistry inside the fuel layer is qualitatively modelledon the basis of a general knowledge of the nitrogen chemistry under differentconditions, such as:

• HCN and NH3 forms NO at high oxygen concentration and temperature• HCN and NH3 reduce NO at low oxygen concentration and high temperature


• CO reduces NO in presence of char if the oxygen concentration is very low• the char acts as a catalyst for the reduction of NO by HCN and NH3

From experiments on single particles following can be assumed• fuel nitrogen bound to the volatiles forms HCN and NH3

• fuel nitrogen bound to the char residue forms NO• around half of the fuel nitrogen is bound in the char residue, Leppälahti 1995,

Saastamoinen 1997.

Reaction kinetics can be found for NO reduction over char surfaces for differentbiofuels, Zevenhoven (1998), and for coal char, Johnsson (1990), which makes itpossible to model the NOx formation and destruction in the char layer. What entersthe char layer from the reaction front is unknown. The situation inside the reactionfront is very complex, the volatiles are released inside the particles, probably as HCNand NH3 and already inside the particles some of it is converted to NO or N2. Thisgas mixture leaves the surface of the particle into a gas stream, which has an oxygenconcentration between 0 and 21% and a temperature between 600 and 1500K. Thereaction front is not modelled in detail and therefore a model based on kinetic data ofvarious reactions can not be established. Instead a model based on split factors isdeveloped. The first split factor gives the part of the fuel nitrogen that is releasedtogether with the volatiles. The first part of the reaction front, where the oxygen stillnot is consumed, is defined as an oxygen-rich region and the subsequent region ofthe reaction front, where the oxygen more or less is consumed, is defined as anoxygen-lean region. In the oxygen-rich region HCN and NH3 most likely form NO, andin the oxygen-lean region this NO to some extent is reduced by the HCN and NH3

leaving the particles. The second split factor defines the fraction of fuel nitrogen thatleaves the particles in the oxygen-rich region. The third split factor defines the degreeof conversion of HCN and NH3 to NO in the oxygen-rich region. The fourth splitfactor, the last of the split factors, is defined as reduction of NO by HCN and NH3,where the split factor is based on the lowest concentrations of NO and the sum of theconcentrations of HCN and NH3.

5.1 Description of nitrogen chemistry model in fuel layer

The model for the nitrogen chemistry in the fuel layer assumes that all NOx is fuelnitrogen. The nitrogen chemistry in the fuel can be separated into the reaction frontand the char layer. The reaction front is also separated in to two regions dependenton the oxygen concentration. In the first region, the oxygen rich region HCN and NH3

are assumed to produce NO:

HCN NH O NO, .3 2 5+ → I

and in the second region, the oxygen lean region HCN and NH3 are assumed toreduce NO:

HCN NH NO N H O CO, .3 2 2 5+ → + + II


If all oxygen is consumed in the reaction front the reduction of the nitrogen oxidescontinues in the char layer above the reaction front and is catalysed by the charsurfaces:

HCN NH NO N H O CO

NO CO N CO

char

char

, .

.

3 2 2

2 2

5

5

+ → + +

+ → +

III

IV

If the oxygen not is consumed oxidation of NH3 and HCN to NO and N2 will takeplace.

After the drying and devolatilization is completed and only char combustion takeplace. During the char combustion all fuel-bound nitrogen is assumed to form NO.This assumption give that in this area of the grate no NH3 or HCN are present andthe only mechanism for the reduction of NO is reaction 5.IV.

The nitrogen chemistry in the reaction front is modelled in three steps and thereactions are modelled by split factors that are put manually. θ is used for the splitfactors and subscript 0 indicates particle surface,1 oxygen rich region, 2 oxygen leanregion and 3 char layer. The oxygen rich region is:

x J x J J J

J x J

J x J x J

J x J

N N NO NH HCN

N N

NO NO NH HCN

NH HCN NH HCN

F dev1 1 0 0 0

1 1 0

1 1 0 1 1 0

1 1 1 0

2 3

2 2

3

3 31

, , , ,

, ,

, , ,

, ,

= + +

=

= +

= −

+

+

+ +

3 8

1 6θ

θ

(5.1)

x is the fraction of volatile gases entering the oxygen rich region. The oxygen leanregion is modelled:

1 1

1 1 1

1 1 1

1 1 1

1 1 0 0 0

2 1 1 0 2 1 1 1 0

2 1 0 1 2 1 1 1 0

2 2 1 1 1

2 3

2 2 2 3 3

3 3

3 3

− = − + +

= + − + + − −

= − + − + − −

= − + − −

+

+ +

+ +

+ +

x J x J J J

J J x J J x J

J x J J J x J

J J x

N N NO NH HCN

N N N NH HCN NH HCN

NO NO NO NH HCN NH HCN

NH HCN NH HCN

F dev1 6 1 63 8

1 6 1 61 63 8

1 6 1 61 63 8

1 6 1 61 6

, , , ,

, , , , ,

, , , , ,

, ,

θ θ

θ θ

θ θ J NH HCN0 3, +3 8

(5.2)

The char layer is modelled:

− ∂∂

= +

−∂

∂=+

C

tk k

C

tk

NOR VI R V

NH HCNR V

. .

.3

(5.3)

where the reaction rate are assumed to be similar to the ones of coal given byJohnsson [1990].


kk C k C k

k C k C k

k T

k T

k T

k C C T

R VNO CO

NO CO

R VI NO NH HCN

.

.. .

exp /

.4 exp /

. exp /

. exp /

=+

+ +

= −= ⋅ −= ⋅ −

%&K

'K

()K

*K

= ⋅ −+

1410

67 6070

2 10 20400

8 9 10 31700

2 36 10 10000

1 2 3

1 2 3

1

25

35

6 0 64 0 64

3

1 60 5

0 50 5

0 5

(5.4)

Boundary condition

J J J

J J

NO NO N

NH HCN NH HCN

F char0

0

2

23 3

= +

=,

, , ,

, (5.5)

The residence time tc in for the nitrogen compounds in the char layer is calculatedfrom the integrated mean time for the nitrogen leaving the char tcc and the time forthe gas leaving the reaction front, tcr.

∂ ∂

= ≤ ≤ +IJ x

Jdx x x x

N

N

x

mean s cF char

F char

mean,

,

/. ;

0

0 5 0 (5.6)

t xJ R x T x T x x

Pcc mean

ii

s s c c s c

=+ +∑ 1 6 1 6/

(5.7)

tJ R x T x T

Pcc

ii

s s c c

=+∑ 1 6

(5.8)

tJ t J t

J Jc

N cr N cc

N N

F dev F char

F dev F char

=++

, ,

, ,

(5.9)

Nitrogen species leaving fuel bed

J J t

J J t

J J J J J J J

NO NO c

NH HCN NH HCN c

N N NO F char NO NH HCN NH HCN

3,

3,

3, 212 2 3, 2 3,

3 3

2 2 3 3

=

=

= + + − + +

+ +

+ +, , , ,2 7 3 84 9

(5.10)

5.2. Description of nitrogen chemistry in free-room calculation

The thermal oxidation of molecular nitrogen and the reburning reaction can beneglected in the plants where temperatures do not reach 1800K, and this condition isalways verified in the furnace in exam, where the maximum computed temperaturesdon’t exceed 1620K and the measured ones are even lower. The main contribution toNOx production is therefore the nitrogen contained in the fuel and an importantfraction of the total NOx emission is produced inside the fuel layer itself. Anothercontribution comes from the “prompt” mechanism, which usually plays a minor role.As for the main chemistry, it is not possible to implement all the reactions in thecalculation together with fluid dynamics, but simplified mechanisms are required. Themodels do not include the HCN->NH3 step, and represent all the NOx intermediates


as HCN. The NOx formation and destruction mechanisms are summarised as inFigure 5.4.

Nitrogen chemistry is not yet completely known, and some reaction rates are highlynon-linear functions of temperature and of the reactant concentrations. For thisreason it is difficult to predict exactly the production of nitrogen oxides, because asmall fluctuation of the reaction conditions may cause an important increase of thereaction rates. Such fluctuations are present throughout the furnace, due both toturbulence and to small discontinuities in the fuel and air feed, and cannot bemodelled in detail, impeding an exact estimation of the total NOx formation. To takeinto account the effect of the turbulent fluctuations a probabilistic approach is used.This consists of evaluating the mean production inside each cell, weighing thereaction rate function with the probability density function of the temperature. Thetemperature probability density function is a beta function, the main value is the onecomputed by the averaged equations, and the variance is expressed as a function ofthe turbulent variables.

+ CH i (prompt) N2

+NO

+ NH i

HCN NH3 + O (thermal)

+OH

+ CH i (reburning) NO:Figure 5.4 Description of the model for the nitrogen chemistry in FLUENT. HCN, NOand N2 are used as in and out-put data.

6. Experimental

The measurements described in the contract was planned before the plant was built,and the estimated cost and time for the measurements were based on experiencefrom a boiler of the same scale as the one in Trollhättan. This estimation turned outto be too optimistic both concerning time and expenses, because of very high costrequired to run the boiler independent of the heat demand from the district heatingsystem. To optimise the activities, considering the funding given, characteristicoperation conditions were defined and much more detailed measurements wereperformed during these test conditions than what was originally planed. By doing sothe quality of the comparison between the simulations and the measurements wasmaintained in a satisfactory way.


The first measurement campaign in Trollhättan the survey measurements, was themain measurement in this project. This survey included 49 permanent measurementpositions and 81 positions for probe. During the test, fuel samples were takencontinuously and analysed. The measurement period was 75 hours for thepermanent positions, 5 minutes per position for the cold suction probe and zirconiacell probe, and 10 minutes per position for the hot suction probe. In all positions 10seconds mean values were logged continuously, except for the FTIR, which gave twomean values during a 10 minutes period, and the zirconia cell, for which 40 valuesper second were collected. For the survey measurements, special, well prepared fuel(pure wood chips) was ordered and the test furnace had to be specially trimmed.Since the probe measurements only took place during short periods it was importantto have stable operating conditions for the whole test period in order to achieve arepresentative picture of the combustion chamber. This was possible in almost alltests. Some disturbances did occur however, most probably due to a temporarychange of the fuel size and moisture content. During these periods themeasurements were paused.

Apart from the survey measurements some additional measurements were carriedout using the normal fuel, consisting of 40% bark, 40% wood chips and 20%sawdust. Ten water-cooled probes were inserted simultaneously in the upper part ofthe combustion chamber above the “neck” to achieve data on temperatures and gasconcentrations of O2, CO2, CO, NO and THC for validation of the modelling. Anadditional cooled suction probe that allowed a much higher suction flow verifiedprevious temperature measurements. The direction of the gas flow along onehorizontal position above the neck was also measured.

7. ResultsThe results consist of two parts: the results from the fuel layer, the free-roomcalculations and the measurements, and a comparison between modelling andmeasurements

7.1 Result of Bed modelIn Figure 7.1 an example of a simulation of the fuel layer can be seen. The primarygas flow of nitrogen, oxygen and water vapour is kept on a low level in the first part ofthe grate allowing the combustion to start. The primary gas flow is then raised inorder to increase the combustion intensity in the fuel layer. When the reaction frontreaches the surface of the grate, the gas flow and the velocity of the fuel layer alongthe grate are decreased to allow the char layer to build up and to increase theresidence time of the gas. Dependent on the reduction of the content of char in thefuel layer, a further reduction of the primary air is necessary before the end of thegrate to keep up the temperature and for the final burn out. In this the profile of theequivalent radiation temperature from the free-room is assumed. The output from thefuel layer model is the position of the reaction front and the height of the fuel layer.

At half way along the grate, the height of the fuel layer rises. In Figure 7.1 this riselooks rather dramatic and unrealistic, but this is a result of the reduction of thevelocity of the fuel layer along the grate and is emphasised by the vertical scale ofthe diagram. The major gas components in the part of the fuel layer where the


reaction front develops are water vapour and nitrogen, whereas oxygen is consumed.In the part where only char combustion takes place, the oxygen concentration firstfalls as a consequence of the increased height of the fuel layer and the decreasedprimary gas flow. Then it rises, while the char is gradually consumed. When theprimary gas flow once more is reduced the oxygen concentration again falls and thenrises slowly as the char combustion continues. The gas is assumed to leave the fuellayer at the temperature of the surface of the fuel layer. The simulation shows thatthe surface temperature of the fuel layer is lower and in some parts much lower thanthe temperature inside the fuel layer, especially during char combustion.

In Figure 7.2 the result of the post-processing of the nitrogen chemistry presented.With the reaction rates of the model, the reduction of NO in the char layer is small,somewhere between 0 and 20% dependent on the char layer surface and gas flowthrough the layer. When the reaction front is not present, the reduction is neiglibledue to the low temperature. Obviously, the nitrogen compounds leaving the fuel layerare already determined in the reaction front, and given by the assumed split factors.Otherwise the model behaves as expected; the reduction of NO is related to theresidence time in the char layer and the temperature. An increased residence timeand temperature increases the reduction of NO.

0 2 4 6 80

0.2

0.4

0.6

0.8

1

Length along grate [m]

Fue

l-N c

onve

rted

to N

Ox,

HC

N o

r N

H3

0 2 4 6 80

150

300

450

Length along grate [m]

NO

and

NH

3+

HC

N [p

pm] NO

NH3

Figure 7.2. Result of the nitrogen chemistry simulation. Left figure, concentration ofnitrogen oxides, and NH3+HCN. Right figure, fraction of fuel nitrogen converted tonitrogen oxides or NH3+HCN

7.2 Result of the free-room model

The aim of the simulation was to find a steady state solution. The algorithm, though,did not converge. Instead of a trend towards a single value, a non-decayingoscillation could be observed. In order to eliminate the fluctuations, many differentoptions of the numerical solver were tried, but without success. This behaviour is dueto the instability of the physical flow, which does not evolve to the exact equilibrium,but oscillates around it. Such instability is quite realistic in flows with gas jets, andoscillations of the flow can actually be observed by looking into the boiler. It isreasonable to say that this is an instability of the turbulent type, which may not beaccounted for by the k and ε model, since it includes vortexes which are much largerthan the control volumes, and that hinder the convergence to a steady state solution.


0

400

800

1200

1600

2000T

empe

ratu

re [K

]

0

2

4

6

8

10

Out

goin

g M

olar

Flo

w [m

oles

/s]

0

0.1

0.2

0.3

0.4

0.5

Bed

hei

ght [

m]

0 1 2 3 4 5 6 7 80

2

4

6

8

10

Bed length [m]

Ingo

ing

Mol

ar F

low

[mol

es/s

] (In

put)

Char layerSurface layerSurrounding (Input)

CH4

COO

2CO

2H

2O

N2

0

0.2

0.4

0.6

0.8

1

Rel

ativ

e m

ass

loss

[−]

Bed surfaceReaction frontMass loss

0 1 2 3 4 5 6 7 80

1.5

3

4.5

6

7.5

Bed

vel

ocity

[mm

/s] (

Inpu

t)N2 (Input)

O2 (Input)

H2O (Input)

Bed vel. (Input)

Velocity change bedVelocity change gas

Figure 7.1 Input data and result of modelling. The grey areas indicate the givenchanges in the primary airflow and velocity of the fuel layer along the grate.


The time variable must therefore be introduced in the calculation, in order to obtainconvergence. This complicates dramatically the solution of the problem, that grows toa size n times larger than a steady state solution, where n is the number of timesteps necessary to describe the full evolution of the flow in time. A solution of thissize is not practically storable in memory, but this is not a significant limitationbecause it would be practically impossible to analyse such amount of data. Thealternative is to monitor (i.e. store the value at every time step) some variable in afinite set of points.

In order to understand the nature of the fluctuations it is also possible to store thevalues of a variable on a whole surface, and visualise it as a contour diagram. Byplacing the images for each time step in a sequence, it become possible to animatethe result, which provides an easily interpretable representation of the unsteadycombustion process.

Figure 7.3 Sections used to display result. Grey planes illustrate the sections

The overall look of the various fields (velocity, temperature, concentrations) does notvary very much with time, so it is possible to make relevant considerations on theflow looking at a single frame of the animation even if it does not represent the wholesolution. Two vertical sections of the boiler, shown in the Figure 7.3, are used fordisplaying the result from the free-room calculation. The velocity vectors on thevertical section parallel to the jets show the presence of a large vortex in the upperpart of the furnace, see Figure 7.4. The presence of a downward flow inside thecombustion chamber is seen, and has been reported from a similar furnace in Mjölby,Schuster 1994. Such a vortex causes an internal recirculation of a part of the fluegases, that therefore have a longer residence time inside the combustion chamberthan the flue gas which goes straight to the exit.


1.62e+03

1.49e+03

1.36e+03

1.23e+03

1.10e+03

9.69e+02

8.39e+02

7.10e+02

5.80e+02

4.50e+02

3.20e+02

Z

Y

X

Figure 7.4 Velocity vectors and temperature field on a vertical section parallel to thejets. The section is shown in Figure 7.3

The difference in residence times is also shown by the temperature field whichincludes a colder area in the middle of the vortex see Figure 7.4, where the gas has alonger time to radiate its energy to the tube walls. Such difference in residenceshould be avoided if possible, even if in this particular case it does not seem to haveimportant consequences. In order to verify the existence of this downward flow aspecial hole in the furnace wall was opened and an appropriate probe was built todetect the direction of the flow. The probe is a 4.7m long steel tube, water cooled toresist the furnace temperatures, which emits a small acetylene jet from the tip. Thejet ignites when introduced into the flue gas flow, due to the high temperature andfollows the flow of the flue gas, if this is strong enough to overcome the buoyanteffect of the hot flame. The flame is clearly visible from the window above the hole,as it is much more luminous than the surroundings, even if sometimes it extinguishesdue to a lack of oxygen. The experiment was carried out twice, in different operatingconditions, and both times it supported the calculation result of a downward flow. Itappears to be a quite strong flow and it is located in a layer, which is approximately0.5 meters thick in the vicinity of the rear wall of the furnace. Extracting the probe alittle at a time the flame follows irregular directions first and it goes upwards later. Theresult of the experiment is therefore completely in agreement with the calculation. Inorder to avoid this vortex, or to decrease the size of the downward flow a rise of theflow from the front secondary air inlet and a decrease of the one from the rear wallsecondary air inlet should be a sufficient remedy that would not imply anymodifications of the plant itself. The velocity and temperature fields on the verticalsection perpendicular to the jets show another feature of the flow that causesdifferent residence times, see Figure 7.5.


Figure 7.5 Velocity vectors and temperature field on a vertical section perpendicularto the jets. The section is shown in Figure 7.3

The pyrolysis gases are passing through the front recirculation jets along thesymmetry plane of the boiler and beside the walls. This causes the combustibles tobe more concentrated in these zones, and the temperature to be higher when theflow meets the secondary combustion air. The displacement of the combustibles tothe sides of the furnace is clearly observed in the concentration measurements. Animprovement of the homogeneity of combustion could be obtained using a morerational spacing of the jets. The temperature contours on the section parallel to thejets also show the presence of a high temperature area around the first part of thefront recirculation jets. This may be due to the high oxygen concentration comingfrom the evaporation zone, that is blown in the hot pyrolysis gas flow, and reactsquickly thanks to the high turbulence.

7.3 Result measurement

The results from the survey measurement can be summarised as follows:1. Reducing conditions measured by the zirconia cell probe in holes 1 and 2 position

a,b,c, Figure 7.6 corresponds well to a relatively low O2 concentration, Figure 7.7and high concentrations of CO2, CO and THC, Figures 7.8-10. The measurementin holes 1 and 2 are in the flame zone above the grate, where the main part offuel volatiles burns, Figure 1.1. Further down along the grate the char residueburns (burn-out zone) and the gas phase above the grate always show oxidisingconditions, Figure 7.6. In this area the O2 concentration is high, Figure 7,7. TheCO2, CO THC concentrations are low, Figures 7.8-10, in relation to what wasmeasured in the flame zone.


2. The temperatures at level 1 are shown in Figure 7.11. Higher temperatures wereexpected in the flame zone in comparison with the results obtained above theburn-out zone. This was also obtained with some exception, hole 1, position A, Band hole 2, position B, Figure 7.11. The reason for the low temperatures in thesepositions is that flue gas is re-circulated from a nozzle located above the grate.The effect of the flue-gas re-circulation can also be seen in the temperaturemeasurement carried out at level 2, hole 7, position A, B and C, Figure 7.12where a temperature level between 190-300 °C was found. As a contrast to theselow temperatures was the highest temperature measured in hole 8, position D(835 °C), see Figure 7.12. It seems likely that oxygen and volatiles are pressed tothe sides by the flue-gas re-circulation, mixed and burned up along the wall.

3. Combustion gases (of various mix between oxygen and unburned species, andwith various extent of burnout) from the lower part of the combustion chamber ismixed with re-circulated flue gas and secondary air in the restriction (the “neck”,see Figure 3.1). The combustion gases have different content depending on their“history” whether they originate from the drying zone in the beginning of the grate,the flame zone or the burn-out zone. When the gases pass the “neck” anintensive combustion takes place leading to a large decrease of the levels of COand total hydrocarbons (THC), down to levels between 0.1-0.4%, Figures 7.13and 7.14. At the same time the CO2 concentration increases from levels between11-14% up to 15-17% despite the fact that the total volume of combustion gasincreases as a result of the secondary air injection.

4. By the measurement of the gas concentrations at level 4, Figure 7.16 and acomparison of the CO-levels at level 3, Figure 7.15 is it possible to follow theburnout of the gas phase in the upper part of the combustion chamber. Thetemperature is still high at this level, especially in the 10 measurement locations,holes 16-20, positions A and B, Figure 7.17. These positions form a core of thecross-section, where the temperature was measured to 839-909 °C. The levels ofCO and THC also decrease from a concentration of 1000-4000 ppm at level 3,Figure 7.15 to only 40-500 ppm at level 4, Figure 7.16.

5. With the nitrogen content measured in the fuel (0.1 % by weight measured on thecombustibles matter) a theoretical level of 280 ppm NH3 and/or NO can beachieved at an excess air ratio of 1.2. If the fact that the gas flow through thegrate is lower than that required for an excess air ratio of 1.2 is taken into account(despite the flow of re-circulated flue gas) then the sum of NO and NH3 in hole 1and 2 ought to be in the range of 400 to 600 ppm. The highest level of the sum ofNO and NH3 was measured to 100 to 200 ppm. An important question is whathappened with rest of the fuel nitrogen. One hypothesis is that NH3 and/or NOdecomposes already when the gas passes through the fuel layer on the grate.This should be possible to study separately in a laboratory scale reactor.

6. Above the burnout zone NO levels between 26-58 ppm were found, Figure 7.18.At the same time the CO2 level was measured to only 2.6-5.3 %, Figure 7.8. Thecalculated average of NO and CO2 in hole 3 and 4 is 40ppm and 3.76 %respectively. If one calculates the corresponding average in the flame zone, hole1 and 2, 85.1 ppm NO and 14% CO2 is obtained. Normalising these levels of NOto a fictitious CO2 concentration of 15%, a concentration of 160 ppm NO iscalculated for the measurement above the burnout zone to be compared to only91 ppm NO above the flame zone, Figure 7.19. This difference is interpreted asan effect of a higher degree of oxidation to NO of the fuel nitrogen during the char


burnout compared to the case when the volatile part of the fuel is oxidised in theflame zone. This interpretation is consistent with the hypothesis that NH3 and/orNO are decomposed already when the combustion gases pass the fuel bed, sincethis lowers the fuel nitrogen conversion to NO. During the char burnout differentconditions prevail on the grate in comparison with the situation in the flame zone.Most of the fuel layer in the burnout zone of the grate consists of ash. In the flamezone the fuel concentration is much higher, and this increases the probability thatthe NO being formed in the gas phase between the fuel particles is reduced onthe passage through the bed.

7. The passage of combustion gases through the “neck” has already beencommented on. The highest temperatures were measured along the rear walldownstream of the “neck”. In these positions also the highest levels of NO wereobtained. This means that the temperature levels in the flame zone are ofimportance for the formation of NO. Since the concentration of NH3 is low, it islikely that some thermal NO formation occurs in the flame zone. From this, it canbe concluded that the flue gas re-circulation plays an important role in order toprevent too high temperatures of the gas phase during its passage through the“neck”.

8. The average concentration of NO measured on dry flue gas for the whole testperiod is calculated to 119 ppm. This corresponds to an emission of NO of 84 mgNO2/MJ fuel supplied, which is equal to 129 mg NO2/nm3 at 15% CO2, dry.


0 2 4 6 8< fue l in x (m ) ash ou t >

0 .0

0 .2

0 .4

0 .6

0 .8

1 .0

Tim

e fr

actio

n w

ith r

ed. c

ondi

tions

_ _

2 .8 m from wa ll

1 .9 m from wa ll

1 .1 m from wa ll

0 .2 m from wa ll

Figure 7.6 Time fraction with reducingconditions at level 1 measured at fourpositions from the right wall: A=2.8m;B=1.9m; C=1.1m and D= 0.2m.

0 2 4 6 8< fue l in x (m ) ash ou t >

0

4

8

1 2

1 6

2 0

Ca

rbon

dio

xide

con

c. (

vol-%

,dry

)

_ _

2 .8m fro m w all

1 .9m fro m w all

1 .1m fro m w all

0 .2m fro m w all

Figure 7.8 Carbon dioxideconcentrations at level 1 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m andD=0.2m.

0 2 4 6 8< fu e l in x (m ) ash ou t >

0

4

8

1 2

1 6

2 0

Oxy

gen

con

cent

ratio

n (v

ol-%

,dry

)

_ _

2 .8m fro m w a ll

1 .9m fro m w a ll

1 .1m fro m w a ll

0 .2m fro m w a ll

Figure 7.7 Oxygen concentrations atlevel 1 measured at four positions fromthe right wall: A=2.8m; B=1.9m;C=1.1m and D=0.2m.

0 2 4 6 8< fu e l in x (m ) ash ou t >

0

4

8

1 2

Ca

rbon

mon

oxi

de

con

c. (

vol-%

,dry

)

_ _

2 .8 m from wa ll

1 .9 m from wa ll

1 .1 m from wa ll

0 .2 m from wa ll

Figure 7.9 Carbon monoxideconcentrations at level 1 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m and D=0.2m


0 2 4 6 8< fue l in x (m ) ash o u t >

0

1

2

3

4

5

Tot

al h

ydro

carb

on c

onc.

(vo

l-%,d

ry)

_ _

2 .8 m fro m w a ll

1 .9 m fro m w a ll

1 .1 m fro m w a ll

0 .2 m fro m w a ll

Figure 7.10 Total hydrocarbonconcentrations at level 1 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m andD=0.2m.

0 2 4 6 8< fue l in x (m ) ash ou t >

2 00

4 00

6 00

8 00

Tem

per

atu

re o

f th

e co

mbu

stio

n g

as (

°C)

_ _

2 .8 m from w all

1 .9 m from w all

1 .1 m from w all

0 .2 m from w all

Figure 7.12 Temperatures of thecombustion gas at level 2 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m andD=0.2m.

0 2 4 6 8< fue l in x (m ) ash ou t >

4 00

5 00

6 00

7 00

8 00

9 00

Tem

pera

ture

of t

he c

ombu

stio

n ga

s (°

C)

_ _

2 .8 m fro m wa ll

1 .9 m fro m wa ll

1 .1 m fro m wa ll

0 .2 m fro m wa ll

Figure 7.11 Temperatures of thecombustion gas at level 1 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m andD=0.2m.

0 2 4 6 8< fue l in x (m) ash out >

0

40000

80000

120000

Car

bon

mon

oxid

e co

nc. (

vol-

ppm

,dry

)

_ _

2 .8m from w a ll

1 .9m from w a ll

1 .1m from w a ll

0 .2m from w a ll

Figure 7.13 Carbon monoxideconcentrations at level 2 measured atfour positions from the right wall:A=2.8m; B=1.9m; C=1.1m andD=0.2m.


0 1 2 3 4 5< fue l in x (m) ash out >

0

40000

80000

120000

Car

bon

mon

oxid

e co

nc. (

vol-

ppm

,dry

)

_ _

2 .9m from w a ll

1 .4m from w a ll

0 .1m from w a ll

Figure 7.14 Carbon monoxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m and C=0.1m.

0 1 2 3 4 5< fue l in x (m ) ash ou t >

0

1 000

2 000

3 000

4 000

5 000

Car

bon

mon

oxid

e co

nc. (

vol-p

pm, d

ry))

_ _

2 .9m fro m w a l l

1 .4m fro m w a l l

0 .1m fro m w a l l

Figure 7.16 Carbon monoxideconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m and C=0.1m

0 1 2 3 4 5< fue l in x (m ) a sh ou t >

0

1 00 0

2 00 0

3 00 0

4 00 0

5 00 0

Car

bon

mon

oxid

e co

nc.

(vo

l-ppm

,dry

)

_ _

2 .9 m fro m wa ll

1 .4 m fro m wa ll

0 .1 m fro m wa ll

Figure 7.15 Carbon monoxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m and C=0.1m.

0 1 2 3 4 5< fue l in x (m ) ash ou t >

7 00

8 00

9 00

1 000

Tem

pera

ture

of t

he c

ombu

stio

n ga

s (°

C)

_ _

2 .9m fro m w a l l

1 .4m fro m w a l l

0 .1m fro m w a l l

Figure 7.17 Temperatures of thecombustion gas at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.


0 2 4 6 8< fue l in x (m ) ash ou t >

0

40

80

1 20

1 60

2 00

Nitr

ic o

xid

e co

nc.

(vo

l-pp

m,d

ry)

_ _

2.8 m fro m w all

1 .9 m fro m w a ll

1.1 m fro m w a ll

0.2 m fro m w a ll

Figure 7.18 Nitric oxide concentrationsat level 1 measured at four positionsfrom the right wall: A=2.8m; B=1.9m;C=1.1m and D=0.2m.

0 2 4 6 8< fue l in x (m ) ash ou t >

0

4 0

8 0

1 20

1 60

2 00

Nor

mal

ised

con

c. o

f nitr

ic o

xid

e (v

ol-p

pm,d

ry)

_ _

2 .8 m fro m wa ll

1 .9 m fro m wa ll

1 .1 m fro m wa ll

0 .2 m fro m wa ll

Figure 7.19 Normalised concentrationof nitric oxide for the measurementpositions at level 1.

The results from the additional measurements are compared with the surveymeasurements in Figures 7.20-41 and in Tables 7.1-3 below. Following observationscan be made:

1. The operating conditions were much more stable during the additionalmeasurements compared to the survey measurements despite the higher qualityof the fuel (only wood chips) used the first time. This result in less “spikes” of COin the stack during the additional measurements. See Table 7.1.

2. The nitrogen content in the fuel was much higher for the fuel mix compared to thewood chips fraction only, see Table 7.2. Despite the much higher fuel nitrogencontent the NOx emission did not increase proportionally for the fuel mix, seeTable 7.3.

3. The combustion gas temperatures below the "neck" at level 3 show differenttrends and levels in the two test cases, Figures 7.20 and 7.21.

4. The oxygen profiles in Figures 7.22 and 7.23 measured at the same level, (level3) are more similar but somewhat lower during the additional measurements withthe fuel mix. This is interpreted as somewhat earlier combustion during thesecond test, an observation also supported by the profiles of total hydrocarbonconcentration in Figures 7.28 and 7.29.

5. At the level above the "neck", level 4 the difference in oxygen concentrationbetween the two test cases is even more pronounced, Figures 7.34 and 7.35.


Table 7.1. Emissions of CO.

Survey measurement Additional measurement16% of the time was the CO levlel above500 ppm.

No "spikes" of CO above 500 ppm.

Conclusion: Large variations in the COlevel obtained during the measurement.

Conclusion: Much more stable operatingconditions.

Table 7.2. Operating conditions during the measurements.Survey test Additional test

Fuel High quality woodchips

Mix of 40% wood chips, 40% bark and 20%saw dust

N-cont. in fuel 0.1% on m.a.f. 0.4% on m.a.f.Load 100% 100%Excess air ratio 1.2-1.3 1.2Primary air/ totalair

0.52 0.54

Flue gas recirc/total air

0.10 0.21

Table 7.3. Emissions of NO.

Survey test Additional test112 ppm (@ 6% O2, dry) 131 ppm (@ 6%O2, dry)55 mg NO/MJ 69 mg NO/MJ84 mg NO2/MJ 106 mg NO2/MJ146 mg NO/m3

n (@15%CO2,dry)

175 mg NO/ m3n (@15% CO2,dry)

224 mg NO2/ m3n (@15%

CO2,dry)269 mg NO2/ m

3n (@15% CO2,dry)

Fuel-N conv. to NO: 46% Fuel-N conv. to NO: 14%


0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

700

800

900

1000

Tem

pera

ture

(°C

)

_ _

2 .9m from w a ll

1 .4m from wa ll

0 .1m from w a ll

Figure 7.20 Temperatures of thecombustion gas at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

2

4

6

8

10

Oxy

ge

n co

nce

ntr

atio

n (

vol-%

,dry

)

_ _

2.9m fro m w all

1.4 m from wall

0 .1m from wa ll

Figure 7.22 Oxygen concentrations atlevel 3 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. First measurement withwood chips.

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

700

800

900

1000

Tem

pera

ture

(°C

)

_ _

2 .9m from w a ll

1.4m from w a ll

0 .1m from wa ll

Figure 7.21 Temperatures of thecombustion gas at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

2

4

6

8

10

Oxy

ge

n co

nce

ntr

atio

n (

vol-%

,dry

)

_ _

2.9m from wall

1 .4 m from wa ll

0.1m fro m w all

Figure 7.23 Oxygen concentrations atlevel 3 measured at different positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. Second measurementwith a mix of biofuel.


0 1 2 3 4 5< fue l in x (m ) ash out >

0

4

8

12

16

20

Car

bon

dio

xide

co

nc.

(vol

-%,d

ry)

_ _

2.9m from w all

1.4m from w all

0.1m from w all

Figure 7.24 Carbon dioxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

1000

2000

3000

4000

5000

Car

bon

mon

oxi

de c

onc.

(vo

l-pp

m,d

ry)

_ _

2 .9m from w a ll

1 .4m from wa ll

0 .1m from w a ll

Figure 7.26 Carbon monoxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

4

8

12

16

20

Car

bon

diox

ide

conc

. (vo

l-%,d

ry)

_ _

2.9m fro m wa ll

1.4m from w all

0 .1m from wa ll

Figure 7.25 Carbon dioxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.

0 1 2 3 4 5< fue l in x (m ) ash ou t >

0

1 000

2 000

3 000

4 000

5 000

Car

bon

mon

oxid

e co

nc. (

vol-p

pm,d

ry)

_ _

2.9m fro m w all

1 .4 m from wall

0.1m fro m wa ll

Figure 7.27 Carbon monoxideconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.


0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

2000

4000

6000

Tot

al h

ydro

carb

on

conc

. (vo

l-ppm

,dry

)

_ _

2.9m from w a ll

1 .4m from wa l l

0 .1m from w a ll

Figure 7.28 Total hydrocarbonconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fue l in x (m ) ash ou t >

0

40

80

1 20

1 60

2 00

Nitr

ic o

xide

con

c. (

vol-p

pm,d

ry)

_ _

2 .9m fro m w a ll

1 .4 m from w a l l

0 .1m from w a ll

Figure 7.30 Nitric oxide concentrationsat level 3 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. First measurement withwood chips.

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

2000

4000

6000

To

tal h

ydro

carb

on c

on

c. (

vol-

ppm

,dry

)

_ _

2 .9m from w a ll

1 .4m from wa ll

0 .1m from w a ll

Figure 7.29 Total hydrocarbonconcentrations at level 3 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.

0 1 2 3 4 5< fue l in x (m ) ash ou t >

0

40

80

1 20

1 60

2 00

Nitr

ic o

xide

co

nc.

(vol

-pp

m,d

ry)

_ _

2.9m fro m wa ll

1 .4m from w all

0.1 m fro m wa ll

Figure 7.31 Nitric oxide concentrationsat level 3 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. Second measurementwith a mix of biofuel.


0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

700

800

900

1000

Tem

pera

ture

(°C

)

_ _

2.9m from w a ll

1 .4m from w a ll

0.1m from w a ll

Figure 7.32 Temperatures of thecombustion gas at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

2

4

6

8

10

Oxy

ge

n co

nce

ntr

atio

n (

vol-%

,dry

)

_ _

2.9m fro m w all

1.4 m from wall

0 .1m from wa ll

Figure 7.34 Oxygen concentrations atlevel 4 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. First measurement withwood chips.

0 1 2 3 4 5< fu e l in x (m ) as h o u t >

7 0 0

8 0 0

9 0 0

1 0 0 0

Te

mp

era

ture

(°C

)

_ _

2 .9 m fro m w a ll

1 .4 m fro m w a ll

0 .1 m fro m w a ll

Figure 7.33 Temperatures of thecombustion gas at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.

0 1 2 3 4 5< fue l in x (m ) a sh o u t >

0

2

4

6

8

1 0

Oxy

gen

conc

ent

ratio

n (v

ol-%

,dry

)

_ _

2 .9 m fro m w a ll

1.4 m fro m w a ll

0 .1 m fro m w a ll

Figure 7.35 Oxygen concentrations atlevel 4 measured at three differentfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. Second measurementwith a mix of biofuel.


0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

4

8

12

16

20

Car

bon

diox

ide

conc

. (vo

l-%,d

ry)

_ _

2.9m fro m w all

1.4 m from wall

0 .1m from wa ll

Figure 7.36 Carbon dioxideconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

1000

2000

3000

4000

5000

Ca

rbon

mon

oxid

e co

nc. (

vol-p

pm,d

ry)

_ _

2 .9m from wa l l

1 .4m from w a ll

0 .1m from w a ll

Figure 7.39 Carbon monoxideconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

4

8

12

16

20

Car

bon

diox

ide

conc

. (vo

l-%,d

ry)

_ _

2.9m fro m wa ll

1.4m from w all

0 .1m from wa ll

Figure 7.38 Carbon dioxideconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

1000

2000

3000

4000

5000

Ca

rbon

mon

oxid

e co

nc. (

vol-

ppm

,dry

)

_ _

2 .9m from w a ll

1 .4m from wa l l

0.1m from w a ll

Figure 7.40 Carbon monoxideconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel


0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

400

800

1200

1600

2000

Tot

al h

ydro

carb

on c

onc

. (vo

l-ppm

,dry

)

_ _

2 .9m from w a ll

1 .4m from w a ll

0 .1m from w a ll

Figure 7.40 Total hydrocarbonconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m. Firstmeasurement with wood chips.

0 1 2 3 4 5< fuel in x (m ) ash out >

0

40

80

120

160

200

Nitr

ic o

xide

con

c. (

vol-

ppm

,dry

)

_ _

2 .9 m from w a ll

1 .4m from w a l l

0 .1m from w a ll

Figure 7.42 Nitric oxide concentrationsat level 4 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. First measurement withwood chips.

0 1 2 3 4 5< fu e l in x (m ) a s h o u t >

0

400

800

1200

1600

2000

Tot

al h

ydro

carb

on

conc

. (vo

l-ppm

,dry

)

_ _

2 .9m from w a ll

1 .4m from wa ll

0 .1m from w a ll

Figure 7.41 Total hydrocarbonconcentrations at level 4 measured atthree positions from the right wall:A=2.9m; B=1.4m; and C=0.1m.Second measurement with a mix ofbiofuel.

0 1 2 3 4 5< fuel in x (m ) ash ou t >

0

40

80

120

160

200

Nitr

ic o

xide

con

c. (

vol-p

pm,d

ry)

_ _

2 .9m from w a l l

1 .4m from w a ll

0 .1m from w a l l

Figure 7.43 Nitric oxide concentrationsat level 4 measured at three positionsfrom the right wall: A=2.9m; B=1.4m;and C=0.1m. Second measurementwith a mix of biofuel.


7.4 Comparison between model calculation and measurementsComparison between the survey measurements during operation with pure woodchips and the simulation is seen in Figures 7.44 to 7.50, for the temperature and gasspecies O2, CO2, CO, NO and total hydrocarbons at all measurement levels and NH3

at level 1 and 2. The measurement levels are presented in Figure 3.1. The followingobservations can be made:

• The simulation predicts the temperature to be approximately 300°C higher than themeasured temperature at level 1 and 2. This is due to unstable operation of the boilerduring the time for these measurements. However, the calculation and themeasurement predict the same trend: the temperature decreases towards the ashoutlet see Figure 7.44. At level 3 and 4 the temperature measurements were made atstable operating condition and the agreement of between the measurement andcalculation is good

•The oxygen concentration is lower in the simulation than in the measurements,especially towards the ash outlet. This indicates that the fuel layer model predicts thechar combustion to be extended further along the grate than it was during themeasurements. In the main part of the fuel layer the agreement between thesimulation and the measurements is good except at the wall, where there probably isa by-pass of the primary gas that can not be described by the present fuel layermodel, see Figure 7.45. At level 3 the agreement between measurement andcalculation is good, but at level 4 the measurements shows twice as much oxygen asthe calculation. In this case the measurements are probably wrong, because all fuelis finished and the oxygen level in the stack is just half of the level at the outlet fromthe furnace. The reason for the measurement error is most certainly air leakage intothe measurement system. The air leakage flow is estimated to 30% of the flue gasflow out from the probes.

• As can be expected the carbon dioxide behaves opposite to the oxygen. This isseen both from the simulation and the calculation, Figure 7.46. A good agreementbetween calculation and measurement is achieved at level 3 and 4, if the measuredconcentrations on level 4 are compensated for the air leakage in the measurementsystem.

• The simulation predicts much lower concentrations of carbon monoxide and totalhydrocarbons than what are measured, Figure 7.47 and 7.48. In the simulation arecarbon monoxide and total hydrocarbons released closer to the fuel chutes then themeasurements show. Compared with the carbon dioxide, the rate of oxidation seemsto be too high. The burn-out along the furnace is the same both, for in calculation andin the measurements. The concentration of unburnt is high in the low levels. A largereduction is obtained between level 2 and 3. Between level 3 and 4 the concentrationof unburnt is further reduced to very low levels

• The nitrogen oxides in the simulation are much higher than the measured values,Figure 7.49, but both give the same trend along the grate. A good agreementbetween simulation and measurement is obtained for the ammonia concentration,


Figure 7.50. The over prediction of the simulated nitrogen oxides is a result of theassumed high conversion of fuel bound-nitrogen to nitrogen oxides in the fuel layermodel. The measurement does not show any dilution effect between level 2 and 3,which is very clear in the simulation. Either the measured concentration is too low inthe lower part of the furnace or nitrogen oxides are formed in the area between level2 and 3.

0 2 4 6 8< fue l in x (m ) a sh ou t >

0

3 0 0

6 0 0

9 0 0

1 2 0 0

1 5 0 0

Tem

pera

ture

(°C

)

_ _ 0 2 4 6 8

< fue l in x (m ) a sh o u t >

0

3 00

6 00

9 00

1 20 0

1 50 0

Tem

pera

ture

(°C

)

_ _

0 1 2 3 4< fue l in x (m ) a sh ou t >

0

3 0 0

6 0 0

9 0 0

1 2 0 0

1 5 0 0

Tem

pera

ture

(°C

)

_ _ 0 1 2 3 4

< fue l in x (m ) a sh ou t >

0

3 0 0

6 0 0

9 0 0

1 2 0 0

1 5 0 0

Tem

pera

ture

(°C

)

_ _

Figure 7.44. Calculated (dotted) and measured (solid) temperature profiles at level 1(upper left figure) and level 2 (upper right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fue l in x (m ) ash out >

0

4

8

12

16

20

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _ 0 2 4 6 8< fue l in x (m ) ash out >

0

4

8

12

16

20

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _

0 1 2 3 4< fue l in x (m ) ash out >

0

4

8

12

16

20

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _ 0 1 2 3 4

< fue l in x (m ) ash out >

0

4

8

12

16

20

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _

Figure 7.45. Calculated (dotted) and measured (solid) oxygen profiles at level 1(upper left figure) and level 2 (upper right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fue l in x (m ) a sh out >

0

4

8

12

16

20

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _ 0 2 4 6 8

< fue l in x (m ) a sh out >

4

8

12

16

20

24

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _

0 1 2 3 4< fue l in x (m ) ash out >

0

4

8

12

16

20

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _ 0 1 2 3 4


0

4

8

12

16

20

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _

Figure 7.46. Calculated (dotted) and measured (solid) carbon dioxide profiles at level1 (upper left figure) and level 2 (upper right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fue l in x (m ) ash o u t >

0

30 00 0

60 00 0

90 00 0

12 00 0 0

15 00 0 0

Ca

rbo

n m

on

oxi

de

co

nc.

(p

pm

,dry

)

_ _ 0 2 4 6 8< fue l in x (m ) ash o u t >

0

30 00 0

60 00 0

90 00 0

12 00 0 0

15 00 0 0

Ca

rbo

n m

on

oxi

de

co

nc.

(p

pm

,dry

)

_ _

0 1 2 3 4< fu e l in x (m ) a sh ou t >

0

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

Car

bon

mo

noxi

de

conc

. (v

ol-p

pm,d

ry)

_ _ 0 1 2 3 4


0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

Ca

rbon

mo

noxi

de

co

nc.

(vo

l-p

pm,d

ry)

_ _

Figure 7.47. Calculated (dotted) and measured (solid) carbon monoxide profiles atlevel 1 (left figure) and level 2 (right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fu e l in x (m ) ash o u t >

0

1 0 0 0 0

2 0 0 0 0

3 0 0 0 0

4 0 0 0 0

5 0 0 0 0

Tot

al h

ydro

carb

on

conc

ent

ratio

ns (

ppm

, dr

y)

_ _ 0 2 4 6 8< fu e l in x (m ) ash o u t >

0

1 0 0 0 0

2 0 0 0 0

3 0 0 0 0

4 0 0 0 0

5 0 0 0 0

Tot

al h

ydro

carb

on

conc

ent

ratio

ns (

ppm

, dr

y)

_ _

0 1 2 3 4< fu e l in x (m ) a sh ou t >

0

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

To

tal h

ydro

carb

on c

onc.

(vo

l-pp

m,d

ry)

_ _ 0 1 2 3 4


0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

3 0 0 0

Tot

al h

ydro

carb

on c

onc

. (v

ol-p

pm

,dry

)

_ _

Figure 7.48. Calculated (dotted) and measured (solid) total hydro carbon profiles atlevel 1 (left figure) and level 2 (right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fue l in x (m ) ash out >

0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

Nitr

ic o

xid

e co

nc.

(p

pm

, d

ry)

_ _ 0 2 4 6 8< fue l in x (m ) ash out >

0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

Nitr

ic o

xid

e co

nc.

(p

pm

, d

ry)

_ _

0 1 2 3 4< fue l in x (m ) ash out >

0

5 0

1 0 0

1 5 0

2 0 0

2 5 0

3 0 0

Nitr

ic o

xid

e co

nc.

(vo

l-p

pm

,dry

)

_ _ 0 1 2 3 4


0

5 0

1 0 0

1 5 0

2 0 0

2 5 0

3 0 0

Nitr

ic o

xid

e co

nc.

(vo

l-p

pm

,dry

)

_ _

Figure 7.49. Calculated (dotted) and measured (solid) nitrogen oxides profiles atlevel 1 (left figure) and level 2 (right figure), at 0.2m (red, star) 1.1m (green,diamonds), 1.9m (blue, squares) and 2.8m (black, triangulars) from the side-wall, andat level 3 (lower left figure) and level 4 (lower right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 2 4 6 8< fue l in x (m ) ash out >

0

10

20

30

40

50

Am

mo

nia

/hyd

rog

en

cya

nid

e c

on

c. (

pp

m,

dry

)

_ _ 0 2 4 6 8< fue l in x (m ) ash out >

0

10

20

30

40

50

Am

mo

nia

/hyd

rog

en

cya

nid

e c

on

c. (

pp

m,

dry

)

_ _

0 1 2 3 4< fue l in x (m ) ash out >

0

10

20

30

40

50

Am

mo

nia

/hyd

rog

en

cya

nid

e c

on

c. (

vol-

pp

m,d

ry)

_ _ 0 1 2 3 4


0

10

20

30

40

50

Am

mo

nia

/hyd

rog

en

cya

nid

e c

on

c. (

vol-

pp

m,d

ry)

_ _

Figure 7.50. Calculated (dotted) and measured (solid) ammonia profiles at level 1(left figure) and level 2 (right figure), at 0.2m (red, star) 1.1m (green, diamonds), 1.9m(blue, squares) and 2.8m (black, triangulars) from the side-wall, and at level 3 (lowerleft figure) and level 4 (lower right figure), at 0.1m (red, diamonds) 1.4m (blue,squares) and 2.9m (green, triangulars) from the side-wall


A comparison between the measurements during operation with a mix of biofuels andsimulation is seen in Figures 7.51 to 7.55, for the temperature and gas species O2,CO2, CO, NO and total hydrocarbons at level 3 and 4. The following observations canbe made:

• At level 3, the predicted temperatures are slightly higher than the measured ones(2.9 meters from the wall) as well as lower (1.4 meter from the wall). The shape ofthe temperature profile with the highest temperature in the third hole is correctlymodelled in the positions located 2.9 meter from the wall. At level 4, the calculatedtemperatures are always slightly lower than the measured ones. Figure 7.51

• At level 3 the calculated oxygen concentrations generally become higher in themodel calculations in comparison with the measurements. The opposite is thenexpected for CO2 as confirmed. To a great extent this difference has disappeared atlevel 4, except for the locations close to the wall, Figure 7.52.

• The total hydrocarbons, which is modelled, as CH4 seem to follow the temperaturepredictions at level 3. Modelled hydrocarbon concentrations are lower thanmeasured, in the positions 2.9 meters from the wall, where the higher temperatureswere predicted. For the positions located 1.4 meter from the wall an opposite result isobtained for both temperature and hydrocarbons. At level 4, the hydrocarbonconcentrations are low in measurements as well as in the model calculations. Thecalculated and measured profiles of hydrocarbons can be seen in 7.53 and thetemperature profiles is Figure 7.51.

• The model predicts also in this case a much lower CO concentrations then themeasurements at both levels, Figure 7.54.

• The predicted NO concentrations at level 3 and 4, Figure 7.55, are in the samerange as the measured ones. This good agreement is obtained by assuming lowerconversion of fuel-bound nitrogen to nitrogen oxides in the fuel layer model.


0 1 2 3 4< fuel in x (m ) ash out >

0

200

400

600

800

1000

1200

Te

mp

era

ture

(°C

)

_ _0 1 2 3 4

< fuel in x (m ) ash out >

0

200

400

600

800

1000

1200

Te

mp

era

ture

(°C

)

_ _

Figure 7.51. Calculated (dotted) and measured (solid) temperature profiles at level 3(left figure) and level 4 (right figure), at 0.1m (red, diamonds) 1.4m (blue, squares)and 2.9m (green, triangulars) from the side-wall

0 1 2 3 4< fue l in x (m ) ash ou t >

0

2

4

6

8

10

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _0 1 2 3 4

< fue l in x (m ) ash ou t >

0

2

4

6

8

10

Oxy

ge

n c

on

cen

tra

tion

(vo

l-%

,dry

)

_ _

0 1 2 3 4< fue l in x (m ) ash ou t >

10

12

14

16

18

20

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _0 1 2 3 4


10

12

14

16

18

20

Ca

rbo

n d

ioxi

de

co

nc.

(vo

l-%

,dry

)

_ _

Figure 7.52. Calculated (dotted) and measured (solid) concentration profiles ofoxygen (upper figures) and carbon dioxide (lower figures) at level 3 (left figures) andlevel 4 (right figures), at 0.1m (red, diamonds) 1.4m (blue, squares) and 2.9m (green,triangulars) from the side-wall



0

400

800

1200

1600

2000

To

tal h

ydro

carb

on

co

nc.

(vo

l-p

pm

,dry

)

_ _0 1 2 3 4


0

400

800

1200

1600

2000

To

tal h

ydro

carb

on

co

nc.

(vo

l-p

pm

,dry

)_ _

Figure 7.53. Calculated (dotted) and measured (solid) concentrations profiles of totalhydro-carbons at level 3 (left figure) and level 4 (right figure), at 0.1m (red, diamonds)1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0

1000

2000

3000

4000

5000

Ca

rbo

n m

on

oxi

de

co

nc.

(vo

l-p

pm

,dry

)

_ _0 1 2 3 4


0

1000

2000

3000

4000

5000

Ca

rbo

n m

on

oxi

de

co

nc.

(v

ol-

pp

m,d

ry)

_ _

Figure 7.54. Calculated (dotted) and measured (solid) concentrations profiles ofcarbon monoxide at level 3 (left figure) and level 4 (right figure), at 0.1m (red,diamonds) 1.4m (blue, squares) and 2.9m (green, triangulars) from the side-wall


0 1 2 3 4< fue l in x (m ) ash out >

0

40

80

12 0

16 0

20 0

Nitr

ic o

xid

e c

on

c. (

vol-

ppm

,dry

)

_ _0 1 2 3 4


0

40

80

12 0

16 0

20 0

Nitr

ic o

xid

e c

on

c. (

vol-

ppm

,dry

)

_ _

0 1 2 3 4< fue l in x (m ) ash ou t >

0

10

20

30

40

Hyd

rog

en

cya

nid

e c

on

c. (

vol-

pp

m,d

ry)

_ _0 1 2 3 4


0

10

20

30

40H

ydro

ge

n c

yan

ide

co

nc.

(vo

l-p

pm

,dry

)

_ _

Figure 7.55. Calculated (dotted) and measured (solid) concentration profiles ofnitrogen oxide (upper figures) and hydrogen cyanide (lower figures) at level 3 (leftfigures) and level 4 (right figures), at 0.1m (red, diamonds) 1.4m (blue, squares) and2.9m (green, triangulars) from the side-wall

8. Discussion and conclusion

The conclusion from present result is that the upper part of the furnace above thesecondary air inlet is much easier to model than the lower part of the furnace. Themodel calculation in the upper part of the furnace agrees very well with themeasurements in both cases examined. The secondary air jets determine the gasflow up to the upper part of the furnace, and the gas entering this part is well mixed.This creates a suitable situation for the CFD-calculation and this is also reflected inthe modelling result.

The lower part of the furnace is much more chaotic, which is a reflection of the mixingprocess going on. This part of the furnace is much more difficult to model, with highaccuracy. In the lower part of the furnace there are jets with a high velocity andturbulence intensity, dissipating into a slow gas flow in connection with complexchemical reactions and flames. Both the turbulence and the chemistry is treated in asimplified way in the CFD-calculation, flames are not treated at all. The jets alsocreate an unstable situation, which makes a time dependent solution necessary, andtime mean values have to be calculated for comparison with measurements. The


lower part of the furnace includes also the description of the fuel layer, which in itselfis a simplified model. It is therefore quite reasonable that the agreement betweenmeasurements and model calculations in this part of the boiler is not as good as inthe upper part. Despite all simplifications, gives the CFD calculation a great deal ofinformation. The fuel layer has the greatest importance for the behaviour in the lowerpart of the boiler and the condition in the free-room above the fuel layer is a reflectionof the fuel layer. To validate the fuel layer model measurements close to the surfacealong the grate surface would have been preferred. These kinds of measurementswere not possible to perform in this project, due to the large surface and the limitedpossibility to enter the furnace with probes. Some information can be gained frommeasurements in an experimental pot, but it is not known how to implement thisexperimental result to a moving fuel layer model at present. There is a greatdifference between an industrial grate and a laboratory bed as is most clearly seenfrom the moisture content of the fuel that can be burned in the different facilities.Experiences show that a pot furnace can operate with fuel having moisture content ofup to 40%, while the moving grate in Trollhättan operates with fuel having moisturecontent between 40 and 60%. The general conclusions of the modelling in the lowerpart of the furnace are that:

• the fuel layer model predicts a too early completion of the drying anddevolatilization

• the overlap between drying devolatilization and char combustion isunderestimated

• the oxidation of carbon monoxide and total hydrocarbons is to fast• the reactions related to nitrogen oxides are too slow in the free-room model

The too rapid drying and devolatilization of the model is reflected by the much widerdistribution of measured total hydrocarbons compared to the simulation. Also thedistribution of the carbon monoxide indicates this. It can be seen from the distributionof oxygen, carbon monoxide and carbon dioxide that a greater overlap betweendrying, devolatilization and char combustion must take place in the fuel layer thanwhat is predicted by the model. Close to the ash removal the levels of carbonmonoxide, carbon dioxide are low, and the oxygen concentration is close to that ofthe primary gas. This means that the char combustion has already ended long beforethe ash falls into the ash removal pit. It can be seen from the analysis of the ash thatthe fuel is burned out. On the other hand gives the fuel layer model that the charcombustion continues nearly up to the ash removal. In the central part of the gratethe concentrations of carbon monoxide and total hydrocarbons are high. Thistogether with a low oxygen concentration indicates that much of the oxygen isconsumed by the char combustion. The fitting parameters that are estimated from thetemperature profile on the metal surface of the grate could be misleading. Thereciprocating grate may cause local mixing of the solid fuel that may course thetemperature on the surface of the grate to rise before the reaction front, as defined inthe model, reaches the grate surface. This is probably the reason, why the dryingand the devolatilization are too fast in the model calculation.

The calculated NO concentrations below the “neck” show that there is no activenitrogen chemistry modelled by the free-room model. This is confirmed by the


calculated concentration profiles of HCN. This means that the nitrogen speciesevolving from the grate in the form of NO, NH3 and HCN, modelled as NO and HCN,do not undergo any further reactions in the free-room. The reason for this could bethe relatively low temperatures given by the simulation, much lower than is normallyobtained in modelling of flame combustion, an application where the nitrogenchemistry model probably works better. On the other hand the nitrogen chemistrylinked to CFD-codes is generally of a low quality. This is further discussed by Kilpinenet al. (1997) where (MS20 of this EU-project) two common nitrogen mechanismsused in CFD calculations were compared with a detailed elementary reactionmechanism at 850 and 1100°C. The study shows that the simplified nitrogenmechanisms do not work at the low temperature, while the detailed nitrogenmechanism does predict a conversion of NH3 into NO. The nitrogen compounds inthe present model calculation are merely diluted by the flue gas recirculation and bythe secondary air. The dilution caused by the secondary air and flue gas recirculationin the calculation is not seen in the measurements. As a result nearly 40% of thenitrogen oxides is formed between measurement level 2 and 3, in the area for thesecondary air injection, if the dilution is the same in the real case as in thecalculation. The remaining 60% of the nitrogen oxides are formed in the fuel layer.Both the calculation and the measurement just above the secondary air inlet showthat the temperatures in the region of the secondary air inlet is lower than the oneswhere formation of thermal NOx may take place. Nevertheless, the temperature in theflames that are visually observed, and which are not possible to model with thepresent CFD code or measured by thermocouples, can lead to the formation ofthermal NOx. Another reasons for the formation of NOx, could be that fuel-boundnitrogen leaving the fuel layer as ammonia or in entrained char particles is oxidised toNO when meeting the secondary air between measurement level 2 and 3. Themeasurement can not support any of these hypotheses, because nearly no ammoniawas found close to the fuel layer, and char particles in the free-room was onlyindicated by visual observations (video film).

The conclusion is that the nitrogen oxides can be reduced further by an improvementof the arrangement of the jets of flue gas recirculation and air for final combustion inconnection with the design of the furnace. This can theoretically decrease theemissions of nitrogen oxides with up to 40%. The conclusion from the NOx modellinginside the fuel layer is that the remaining 60% of the nitrogen oxides formed, can bereduced, but better understanding on the formation of the nitrogen oxides and itsprecursors is needed. Special effort has to be made to understand the reaction front.Theoretically a fuel layer of biofuel offers an excellent opportunity to reduce thenitrogen oxides to extremely low levels. During the devolatilization ammonia andhydrogen cyanide are formed and these species can contribute to the reduction ofnitrogen oxides, if the conditions are favourable. By arranging the combustion of thefuel layer in an optimal way, one should be able to create the same situation in thefuel layer and in the lower free-room as recommended for secondary measures, suchas selective not catalytic reduction (SNCR). Also the formation of a char layer abovethe reaction front could improve the NOx reduction performance but this needs to bestudied in more detail in the future both by theoretically and experimental works.


9. References

Fluent Inc. Fluent/UNS 4.2.5 users guide,1997

Gort R. On the propagation of a reaction front in a packed bed, PhD thesis Universityof Twente, ISBN 90-9008751-6, 1995.

Johnsson, J.E. A new NOx module for the IEA-model. 21th IEA-AFBC MeetingBeograd, Department of Chemical Engineering, Technical University of Denmark,1990.

Jones, W.P., Lindstedt, R.P., Global reaction schemes for hydrocarbon combustion.Combustion and Flame, vol. 73, pp. 233-249, 1988.

Kilpinen, P.; Brink, A.; Boström, S.; Mueller, C.; Nordström, T.; Hupa, M.; Simplifiedammonia oxidation mechanism for modelling NOx emission from wood firing – testsat ideal plug flow conditions, Report 97-5, Åbo Akademi, Faculty of ChemicalEngineering, Combustion Chemistry Research Group, 1997.

Leppälahti, J., Formation of NH3 and HCN in slow-heating-rate inert pyrolysis of peat,coal and bark, Fuel, vol.74, pp. 1363-1368, 1995.

Schuster, R. Matematisk modellering, CFD; Stiftelsen för Värmeteknisk Forskning,Report no. 516, ISSN 0282-3772, 1994.

Magnussen, B.F. Hjertager, B.H. On mathematical modeling of turbulent combustionwith special emphasis on soot formation and combustion. 16th Symp. Int. onCombustion, The Combustion Institute, Pittsburgh, pp. 719-743, 1977.

Magnussen, B.F., The Eddy dissipation concept, Division of Thermodynamics,Norwegian Institute of Technology, 1989

Saastamoinen, J.J.; Haukka, P.; Simultaneous drying and pyrolysis in fixed bedcombustion of wet biofuel. Proceedings of the 11th International Drying Symposium(IDS ´98), Halkidki, Greece August 19-22, pp.1975-1982, 1998.Saastamoinen J.J., Horttanainen, M., Taipale, R., Sarkomaa, P., Propagation ofignition front in fuel beds of wood particles, VTT Energy, 1999.

Saastamoinen J.J. Hämäläinen J.P. and Kilpinen P. Release of nitrogen compoundsfrom wood particles during pyrolysis. Proceedings of the Fourth InternationalConference on Technologies and Combustion for a Clean Environment, Clean Air IV,Lisbon, Portugal, pp. 3.1:1-11, 1997.

Zevenhoven, R., Hupa, M., The reactivity of chars from coal, peat and wood towardsNO, with and without CO, Fuel vol.77, pp 1169-1176, 1998.


Appendix A Composition of the volatile

The composition of the volatile gases released from the fuel is unknown. Byassuming that the hydrocarbon in the volatile gases is methane and that the char ispure carbon, the composition of the volatile gases can be estimated. The molarbalance is based on dry and ash-free substance. The ash-free char content of thefuel is:

′ =−

YY

Ycharchar

ash1

The volatile gases are assumed to include carbon dioxide, carbon monoxide,methane and water.CH O n CO n CO n CH n H On m ⇒ + + +1 2 2 3 4 4 2

n and m is

nY

Y Ym

Y

Y YH

C char

O

C char

=− ′

=− ′

12 0 75.

h1 and h2 are normalised heating values of carbon monoxide and methane. Theheating value of the volatile part of the fuel and the normalised heat of devolatilizationis h3 and h4. Normalisation is made so that all values in the matrix are in the sameorder of magnitude,

h I I I

h I I I I

h H M Y I I I

h H M Y I

CO CO CO

CH CO H CO

u C char C CO CO

dev C char CO

O

1

2

3

4

2 2

4 2 2 2

2 2

2

2

1

= −

= − −

= − ′ −

= − ′

3 8

3 8

3 84 91 6

/

/

/

/

Hu is the lower heating value of the fuel and Hdev is the heat of devolatilization. Thecomposition of the volatile gases is obtained by solving the following system ofequations:

1 1 1 0

0 0 4 2

2 1 0 1

0 0

1 12

0 75

1 2

1

2

3

4 3 4h h

n

n

n

n

Y Y

Y Y

Y

Y

h hC char

C char

H

O

!

"

$

####

!

"

$

####

=− ′

− ′

−

!

"

$

####1 6

1 6

.

The enthalpy, heat capacity and molar mass of the volatile gases are:


In I n I n I n I

n n n n

cn c n c n c n c

n n n n

Mn M n M n M n M

n n n n

vol g

CO CO CH H O

pvol g

pCO pCO pCH pH O

vol g

CO CO CH H O

0 5

0 5

0 5

=+ + +

+ + +

=+ + +

+ + +

=+ + +

+ + +

1 2 3 4

1 2 3 4

1 2 3 4

1 2 3 4

1 2 3 4

1 2 3 4

2 4 2

2 4 2

2 4 2

The enthalpy, and molar mass of the volatile solid are:

I I T n n n nH

Mc dT

M M nM mM

vol s vol g refdev

vol spvol s

T

T

vol s C H O

ref

0 5 0 5

0 5

0 5

0 5

1 6= + + + + +

= + +

I1 2 3 4

Appendix B Analytic solution for reactions controlled by mixing

The analytic solution of the system of differential equations:

∂∂

= −+

∂∂

= −+

−

∂∂

= −+

+ +

J

tjX

b

J jtJ J

J

tjX

b

J jtJ J J J

J

t

b

J jtm J J J J

CHCH CH O

COCO CO O CH O

OCH O CO O

m

m m

m

m

0

0

0

12

12

2

2 2

2

2 21

min( , )

min( , ) min( , )

min( , ) min( , )

3 8

0 53 8

for the condition J J J JCH O CO On≤ ≤

2 23 8 3 84 9& ,

JjX J jt

b jC J jt

J C J jtj b j

J jt bj J J jt b jX

bj t J jt X bj J J jt X j J J jt X

bj t J jt X j t J jt X b C J jt

b jC

CHCH b j

CO

b j b j

CH

b j

CH

b j

CO

b j

CO

b j

CO

b j

CO

m

m

m

m

=+

++ +

= + ++

+ + +

+ + + + + + +

+ + + + + + +

+

−

− −

01 0

2 0 2 02

0 0

30

20 0

30 0

30

40

31 0

2

1

2

1 61 6

1 6 0 5 1 6 1 624

1 6 1 6 1 6

1 6 1 6 1 6

/

/ /

/ / /

/ /

/

ln

1 02

1 0

2 2 3

012 2 1 1

1 0

2

2

22

ln ln

ln/

J jt bj C J jt

Jbjt bX jX bmX jmX bX jX

b jC

J jt C C mCbC J jt

j

O

CH CH CH CH CO CO

b j

m m m m

+ + +

=− − + + − −

++ +

+ + + − ++

−

1 6 1 6

3 80 5

1 6 1 6 1 6


for the condition J J J JCH O CO On> ≤

2 23 8 3 84 9& ,

JjX J jt

b jC J jt

Jjt b X bjX b mX b X bjX j X

b j b j

C C J jt C m J jt

Jm J jt bjX J J jt bj X t J jt C b bj j

b j

CHCH b j

CO

CH CH CH CO CO CO

b j b j

O

b j

CH

b j

CH

b j

m

m

m m m

m m

=+

++ +

=+ − + + +

+ ++

+ + + − +

=− + + + + − − −

+

−

− −

−

01 0

2 2 2 2

3 2 0

2

1 0

2

0 0 02

0 12 2

2 2 3 2

2

2

1 3 2

1 6 1 6

3 80 50 5

1 6 1 60 51 6 1 6 1 6 2 74 9

/

/ /

/ / /

0 50 51 6

b j

C J jtb j

++

+ + −

2

2 0

2/

and for the condition J J J JCH O CO On> >

2 23 8 3 84 9& .

J jtX CC J jt

mJ jtX C

J C J jt

CH CH

b m j

CO CH

O

b m j

m m

m

= + −+

−= +

= +

− −

− −

13 0

2 2

2

2 3 0

2 2

2

21 6

1 6

0 5

0 5

/

/

Paper VII

Ignition and propagation of a reaction front in cross-current bedcombustion of wet biofuels

H. Thunman, B. Leckner*

Department of Energy Conversion, Chalmers University of Technology, 412 96 Gothenburg, Sweden

Received 12 May 2000; revised 9 August 2000; accepted 12 August 2000

Abstract

Grate firing is the most common way to burn bio-fuels in small-scale units. Different combustion modes are achieved depending on howfuel and primary air are introduced. In continuous systems fuel and air are usually fed in cross-current and counter-current flow. Here,combustion of wet biofuels is studied in a 31 MW reciprocating grate furnace (a cross-current flow combustor), and additional experimentshave been made in batch-fired pot furnaces. The fuel was forest waste with moisture content of approximately 50%. The combustion in across-current flow furnace is generally assumed to start by ignition on the surface of the bed, followed by a reaction front propagating fromthe surface down to the grate. Measurements and visual observations presented in this paper show, however, that in the case of wet fuels theignition takes place close to the grate, followed by a reaction front propagating from the grate up to the surface of the bed. Hence, the progressof combustion in the bed is opposite to the expected one.q 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Grate combustion; Biofuels; Reaction front

1. Introduction

Grate firing is used to burn bio-fuels in small-scale units.Different combustion behaviours can be achieved depend-ing on how fuel and primary air are introduced. The mostcommon configurations of fuel and air supply in continuoussystems are cross-current and counter-current flow. Anexample of units where fuel and air are introduced accord-ing to the two modes is shown in Fig. 1. In cross-currentflow the fuel is fed at one end of the grate and transportedalong the grate while burning to completion. Primary air isintroduced perpendicular to the grate from below. Theairflow can be controlled separately in each part of thegrate. In counter-current flow the fuel is thrown by a sprea-der or dropped onto the surface of the bed, and the air isevenly introduced through the grate from below.

Combustion in cross-current flow units has beendescribed by several authors [1–5] as taking place in abed, which is heated by radiation from flames and refractorysurfaces above the bed until it ignites on the upper surface.This generally accepted combustion process can bedescribed as follows. After ignition, a reaction front (Fig.1(a)) propagates from the surface of the bed down to the

grate against the direction of the combustion air. The heat,generated in the reaction front, is transported against theflow of combustion air and dries and devolatilises the rawfuel. This allows the reaction front to propagate. Due to thedifferent directions of heat and airflow, the heat is not trans-ported downwards far from the position where it is released,and the reaction front is narrow. The heat generated in thereaction front originates from oxidation of fuel and, if not alloxygen is consumed in the narrow reaction front, a charlayer will be formed above the reaction front. When thereaction front reaches the surface of the grate, a secondaryreaction front, propagating up towards the surface of thebed, burns the char layer previously formed.

The counter-current flow has been investigated more thancross-current flow due to its use in gasifiers. (In Ref. [6] notless than 37 references on modelling of counter-current flowcombustors and gasifiers are presented.) In a counter-currentflow combustor the air is supplied from the bottom and thefuel from the top (Fig. 1(b)). The combustion stages fromthe grate and up through the bed are char combustionfollowed by devolatilisation and drying. When charcombustion takes place upstream of devolatilisation, theheat will be produced over a larger region due to the ratherslow diffusion of oxygen into the char. The hot productgases provide heat for devolatilisation and drying of thefuel during their way up through the bed. In this system

Fuel 80 (2001) 473–481

0016-2361/01/$ - see front matterq 2001 Elsevier Science Ltd. All rights reserved.PII: S0016-2361(00)00127-7

www.elsevier.com/locate/fuel

* Corresponding author. Tel.:146-31-772-1431; fax:146-31-772-3593.E-mail address:[email protected] (B. Leckner).

nearly all volatiles leave the bed unreacted. The supply ofair and fuel creates an even, steady state reaction front,extending over the cross-section of the bed.

In the present work the cross-current flow unit is studiedby combustion of a fuel batch in a pot furnace. The combus-tion time for a fuel batch in a pot furnace corresponds to acertain transport distance on the reciprocating grate, Fig. 2,and the progress of combustion is similar to that of a fuelbatch in the pot furnace. The concept of the travelling potfurnace is a classical approach [5], which is suitable whenthe horizontal velocity of the bed along the grate is fasterthan the vertical velocity of the propagating reaction frontinside the bed, making the two-dimensional effectsnegligible.

The purpose of the present work is to investigate thecombustion behaviour of a cross-current fuel bed burning

wet fuels, such as forest waste. In such cases it can besuspected that ignition takes place close to the grate and,in contrast to the above conventional description, the igni-tion front propagates through the bed in the same directionas the airflow, as shown in Fig. 2(b). The behaviour of alarge-scale fuel bed is investigated by measurements in a31 MW reciprocating grate furnace as well as in potfurnaces.

2. Theory

In order to evaluate the limits of the velocity of the reac-tion front in a fuel batch ignited from one side and with airsupplied from the other, a maximum reaction front velocityis estimated by a heat balance across the reaction front. Heatis transported in the reaction front by thermal conduction,radiation and convection. Due to the opposite directions ofthe reaction front velocity and the airflow, the convectiveheat transfer reduces the heat flux. Here, the interest is in themaximum possible velocity, and therefore the convection isneglected. The radiation and heat conduction are modelledby an effective thermal conductivity of the fuel layer,keff,consisting of a radiative and a conductive constituent [7]:

keff 4nsdsT3 1 1 2 nks 1

where n is the bed voidage,s the Stefan–Boltzmannconstant,ds the particle diameter,T the temperature andks

the thermal conductivity of the fuel, estimated according toMacLean [8]. The maximum heat transport is achieved ifthe temperature rises from the initial temperature,T0, to theadiabatic temperature,Tad, in the reaction front. The effec-tive thermal conductivity is temperature dependent. In thisevaluation of the maximum velocity the effective thermalconductivity is estimated at the adiabatic temperature. Theheat flux across the reaction front must be equal to or smal-ler than the energy contained in the fuel entering the reac-tion front. If the width of the reaction front isx, this gives:

keff;max

xTad 2 T0 # usHrs1 2 n 2

whereus is the velocity of the reaction front,H the lowerheating value of wet fuel per kilogram dry fuel andr s thedensity of dry fuel.H andTad are derived in Appendix A.The maximum velocity of the reaction front is attained whenthe width of the reaction front is minimum. This width isdetermined by the drying timet of the particles:

x ust: 3The maximum velocity of the reaction front is obtained byinserting Eq. (3) into Eq. (2):

us keff;maxTad 2 T0

Hrs1 2 nt

s: 4

In some instances the propagation rate of the reaction front(kg/m2 s) is used instead of the velocity of the reaction front

H. Thunman, B. Leckner / Fuel 80 (2001) 473–481474

Nomenclature

a constant in correlation ofCp (J/kg K)b constant in correlation ofCp (J/kg K2)Cp specific heat (J/kg K)d diameter (m)H heating value (J/kg)h enthalpy at reference temperature (J/mol)M molar mass (kg/mol)n number of moles (–)k heat conductivity (W/m K)T temperature (K)t time (s)u velocity of reaction front (m/s)x width of reaction front (m)X mass fraction in wet fuel (–)Y mass fraction in dry fuel (–)Greekl air-to-fuel ratio (–)n bed voidage (–)r density (kg/m3)s Stefan–Boltzmann constant,

5:67× 1028 W=m2 K4

Subscript(capital letters indicate species)ad adiabaticb boilingc charvap vaporisationi speciesm moisture, moistmax maximumn normal (used to indicate normal cubic meter)eff effectives solidu lowerv volatilesw water0 initial

(m/s). The propagation rate is velocity multiplied by appar-ent density,rs1 2 n; of the packed fuel bed. The dryingtime of a particle is estimated in a simplified way for a one-dimensional slab, exposed to a black surrounding, radiatingwith the adiabatic temperature. The vaporisation ismodelled as a drying front moving from the surface of theparticle to its centre. The radiative heat flux, received by thesurface of the particle, is transported to the drying frontwithin the particle by thermal diffusion. Heat accumulationin the particle is neglected. Under the given conditions the

heat balance of the particle becomes:

sT 4ad 2 T4

s 2ks

ds 2 dmTs 2 Tb

2ddm=2

dtrs

Xm

1 2 Xm

1MH2O

Hvap 1

ZTs

T0

Cp;H2O dT

!:

5The drying time is then:

t 2Z0

d

Xm

1 2 Xm

rs

MH2O

Hvap 1ZTs

T0

Cp;H2O dT

!ds 2 dm

4ksTs 2 Tb ddm 6

whereTs is the temperature of the particle surface,Tb theboiling temperature,ds the particle diameter,dm the moistcore diameter,Xm the moisture content,MH2O the molarmass of water,Hvap the heat of vaporisation, andCp;H2O

the specific heat of water (gas). The velocity (or propagationrate) of the reaction front is given by the adiabatic tempera-ture, which is a function of air-to-fuel ratio and moisturecontent, as shown in Appendix A. Once the velocity (orpropagation rate) is known, the corresponding airflow canbe calculated from the air-to-fuel ratio.

In contrast to the above, a fuel batch that is ignited andsupplied with air at the same side of the bed will not have astable reaction front, unless the batch is very long in thedirection of the airflow. When the bed is ignited, a narrowchar layer is formed. The combustion of this layer producesheat that is transported with the gas flow and devolatilisesand dries new fuel. This expands the layer of char combus-tion and more heat will be produced, resulting in an accel-erating drying and devolatilisation front. A reaction frontwith stable velocity does not develop until the heat producedis equal to the heat needed for drying, devolatilisation and,dependent on moisture content, gasification of some of thechar. The velocity and the length of the stable reaction frontare directly correlated to the airflow. Under the condition ofno external heat losses, combustion can be maintained untilthe theoretical limit of moisture content in the feed fuel issuch that the lower heating value of wet fuel is equal to zero.

For a fuel batch of moderate height the combustion beha-viour differs significantly depending on where ignition takesplace in relation to the location of primary air introduction.Not only the order of the combustion stages will differ, asdescribed in Section 1, but also the behaviour of the reactionfront velocity. A batch ignited from the surface opposite towhere the air is supplied attains a nearly stable reaction frontvelocity, whereas a batch ignited from the same surface asthe air is supplied has a transient reaction front velocity. Thelatter case is the most favourable combustion situation, notonly because the heat flows in the same direction as the gas,but also because the oxygen is consumed in the front,precluding the propagation of a reaction front from the

H. Thunman, B. Leckner / Fuel 80 (2001) 473–481 475

Fig. 2. Principle combustion behaviours in a cross in a cross-current flowunit: (a) if the bed is ignited from the surface of the bed, or (b) from thesurface of the grate. A indicates position of ignition, B vertical section, Creaction front, I unreacted fuel, II drying, III devolatilisation, IV charcombustion or gasification, and V ash.

Fig. 1. (a) Grate with cross-current flow. (b) Grate with counter-currentflow.

opposite side of the bed. Consequently, for ignition on theair supply side, the reaction front propagates with the gasflow through the bed towards the opposite surface of thebed. Except for the top particle layers, which are exposedto radiation from flames and refractories in the freeboard,the combustion is independent of the conditions at the oppo-site side of the bed.

3. Measurements

Measurements in the reciprocating grate furnace weremade for three operating conditions using two types offuel. One fuel was chips of trunk wood with a moisturecontent of 40%, henceforth referred to as pure wood

chips. The other fuel was forest waste (wood chips 40%,bark 40% and saw dust 20%) with a moisture content ofabout 50%. Thermocouples were mounted in drilled holes inthe rods of the grate to measure the surface temperature ofthe grate, in various positions along the grate and gasconcentrations were measured above the surface of thebed. The total hydrocarbon (THC) concentration was deter-mined by a FID (Flame Ionisation Detection) analyser, butconcentrations that exceeded the measurement range of theFID-analyser were analysed by a FTIR (Fourier TransformInfrared) analyser. The furnace and the positions of themeasurement equipment are shown in Fig. 3. The grate is5 m wide and 8 m long. The velocity of the grate wasapproximately 6 mm/s on the first 4 m and then 1 mm/s,resulting in a fuel residence time of 1 h and 15 min in thecombustor. The residence time on the first 4 m was 12 minand the corresponding primary airflow was between 0.1 and0.2 mn

3/s. The primary air was saturated by water at 458C andpre-heated to 1508C before entering the grate. Norecirculated flue gas was added to the primary air. The initialheight of the fuel layer was approximately 0.5 m. Theresults presented here were obtained during a larger projectreported in Refs. [9–11].

Experiments in pot furnaces using the same forest wasteas in the reciprocating grate furnace were carried out at VTT(Technical Research Centre of Finland, VTT-Energy,Jyvaskyla) and at SP (Swedish National Testing andResearch Institute). The measurement set-up at VTT isdescribed in Ref. [12]. The pot furnace has a circularcross-section with a diameter of 244 mm and a height of300 mm. Three thermocouples are introduced into the bed atdifferent heights. The pot furnace at SP is 480× 520 mm2

by cross-section and 700 mm by height and is provided withnine thermocouples introduced into the bed at differentheights. The two furnaces differ mostly in the direction ofthe airflow and the movement of the reaction front; the airmoves upward and the reaction front moves downward atVTT and in the opposite directions at SP. Also, the flue gasmeasurement was carried out upstream of the secondary airinjection at VTT and downstream of this location at SP. Anaverage velocity of the reaction front through the bed can becalculated from these data. The intention was that both unitsshould be operated at the same primary gas flow as used inthe reciprocating grate.

4. Calculation results

The theoretical reaction front velocity, in a bed with airsupply from one side and ignition from the other, is esti-mated by Eq. (4) for 10-mm particles with a dry density of300 kg/m3 (forest waste) and moisture contents varyingbetween 10 and 70%. The bed voidage is assumed to be0.5. This value is a typical average for various particlebeds having voidages between 0.4 and 0.6, depending ontype and shape of the particles [13]. The resulting reaction


Fig. 3. Position of measurements in the reciprocating grate furnace. Gassampling (A), thermocouples (P) (31 MW boiler, Kvaerner Pulping AB).

Fig. 4. Calculated maximum propagation rate of the reaction front fordifferent superficial air velocities. Both propagation rate and air velocityare given by the adiabatic temperature, which is a function of air-to-fuelratio, l , and moisture content. Calculation was made for 10-mm woodparticles with different moisture contents: (a) 10, (b) 30, (c) 50 and (d) 70%.

front velocities can be seen in Fig. 4. The calculation showsthat the reaction front velocity and the airflows for which areaction front exists are very sensitive to moisture content.For the airflows in the reciprocating grate, 0.1 and 0.2 mn

3/s,the moisture content must be less than 45% for a reactionfront to exist. As expected, the lower the moisture content,the higher the velocities of the reaction front can be beforeextinction takes place. The reason is that a raise of themoisture content increases the energy needed for the vapor-isation and decreases the adiabatic temperature. As the heat

transfer mainly comes from radiation, a lower temperaturereduces greatly the reaction front velocity. A maximumreaction front velocity is attained close to stoichiometricconditions. Since the same adiabatic temperature is reachedfor both over and under-stochiometric conditions, the velo-city of the reaction front is the same at two differentairflows, as seen in Fig. 4.

5. Results of measurements

The surface temperature of the reciprocating grate ispresented in Fig. 5, and to give an impression of thecombustion activity, the concentration of total hydrocarbons(THC) above the fuel bed is shown in Fig. 6. In the case ofpure wood chips the temperature rises at a location between1.4 and 1.8 m from the entrance of the fuel. For forest wastethe temperature was high already in the first measure-ment position at 1.4 m. These positions correspond toresidence times on the grate of 4–5 min. The gasconcentrations show that hydrocarbons are releasedearly and that devolatilisation goes on during the first 4–5 m. Computational fluid dynamics calculations includingcombustion verify that the high concentration of hydrocar-bons measured above the front part of the grate is a result ofgas brought there from the bed and not by the stirring of thegas space above the grate [9,10]. The first part of the bed, 1–1.5 m, is visible through a view-glass located in the wall ofthe furnace. In this region there were no flames, but a largeamount of smoke left the bed. There was also no stirring ofthe bed during its transport along the grate in this first visiblepart of the bed.

The measurements at SP are presented in Fig. 7. Theheight of the fuel batch in the pot furnace was 0.5 m. Thesame primary airflow as in the bed of the reciprocatinggrate, 0.16 and 0.27 kg/m2 s, was wanted, but the airflowhad to be reduced to about 0.03 kg/m2 s to maintain a suffi-ciently high temperature inside the bed for propagation ofthe reaction front. After ignition, the reaction front moveddown through the bed layer with a velocity of 0.07 mm/scorresponding to a fuel consumption of 0.012 kg/m2 s(based on dry substance). The measurements at VTT arepresented in Fig. 8. In this case the height of the batchwas 0.3 m. To ignite the fuel at the desired airflows, thefuel was pre-dried from the moisture content of 56.6 to40.3%. Both airflows, 0.16 and 0.28 kg/m2 s, gave thesame velocity and the same behaviour of the reactionfront. The reaction front moved down through the bedlayer with the velocity of 0.05 mm/s corresponding to afuel consumption of 0.008 kg/m2 s (based on drysubstance). When 20% of the mass was gone, the reactionrate increased to 0.16 mm/s corresponding to 0.025 kg/m2 s(based on dry substance).

Results from pot furnace experiments with biofuels[2,4,14], show a similar influence of air velocity. The velo-city of the reaction front (ignition front) increases first with


Fig. 5. Measured time-average temperature on the reciprocating grate.Filled circles indicate measurement with pure wood chips and unfilledcircles are measurement with forest waste.

Fig. 6. Total hydrocarbon concentration above the bed of the reciprocatinggrate. Filled circles indicate the second measurement row and unfilledcircles the first measurement row (cf. Fig. 3). Measurements from operationwith pure wood chips.

increasing air velocity, reaches a maximum, and thendrops slightly until the reaction extinguishes, Fig. 9. Highermoisture content in the fuel decreases the velocity of thereaction front [2,4]. In Fig. 9 the reaction velocities quotedabove are compared with measurements from Ref. [2]. It isobvious that the higher moisture content reduces the velo-city of the reaction front. This agrees with the observationsreported in Ref. [4].

6. Comparison between calculation and measurement

In Fig. 10 the data presented in Fig. 9 are compared withcalculations of the maximum velocity according to Eq. (4)for 10-mm particles. The data of Gort [2] for 10-mm woodcubes with moisture contents of 10 and 30% (curves A and


Fig. 7. Bed mass in pot furnace experiment at SP. Moisture content 56.5%(wet basis). Primary airflow 0.03 kg/m2 s. Solid line is measurement,dashed line fitted mass reduction during the propagation of the reactionfront. The velocity of the reaction front is estimated to 0.012 kg/m2 s (dryfuel).

Fig. 8. Bed mass in pot furnace experiment at VTT. Moisture content 40.3%(wet basis). Primary airflow: (a) 0.16 and (b) 0.28 kg/m2 s. Solid lines aremeasurements, dashed lines represent fitted mass reduction during thepropagation of the reaction front. The velocity of the reaction front isestimated to (I) 0.008 and (II) 0.025 kg/m2 s (dry fuel).

Fig. 9. Propagation rate of the reaction front as a function of air velocity.Experimental data from Gort [2]: 30-mm wood cubes, 10% moisture (A),10-mm wood cubes, 10% moisture (1), and 10-mm wood cubes, 30%moisture (K). Experimental data from forest waste SP, 56.6% moisture(X), and VTT, 40.3% moisture (W). The ignition rate is based on drysubstance.

Fig. 10. Calculated maximum propagation rate of the reaction front for 10-mm wood particles, dotted lines. Solid lines are curve fits of the measure-ments presented in Fig. 9. The measurements are indicated by capital lettersand calculation with small letters, the different moisture contents are indi-cated by: A,a 10% [2], B,b 30% [2], C,c 40.3% (VTT) and D,d 56.6% (SP).

B), measured at several airflows, fit inside the calculatedmaximum velocities of the reaction front. The model isqualitative, based on several simplifying assumptions, butit provides a measure of the theoretical maximum velocitiesof the reaction front for given airflows. At low airflows thesituation in the reaction front agrees with the assumptions ofthe model and there is good agreement between calculationand measurement. For low airflows an insulating char layerdevelops downstream of the reaction front, and all oxygen isconsumed inside the bed, resulting in a low air-to-fuel ratioand consequently a low adiabatic temperature. As theairflow increases the air-to-fuel ratio raises and the charlayer becomes less significant, which enhances the externalheat losses. As the airflow raises further the gas residencetime inside the reaction front is no longer sufficient for thereaction of the volatiles and all heat generation will not takeplace inside the bed. Furthermore, an increasing airflowenhances the convective heat flow between the gas andthe particles, reduces the heat flux across the reactionfront and in the end quenches the reaction front. Since theconvective heat transfer was neglected in the calculationsthe reaction front velocity diverges more and more from thecalculated maximum velocity with an increasing airflow.

In the experiments at SP and VTT the forest waste withhigh moisture content was used. The measured data fit thecalculated values quite well. At the highest moisture content(curve D, 56.6%), the velocity of the reaction front is higherthan the calculated one, but it is inside the limits of accuracyof the model. In this case no reaction front can propagate atthe airflows present on the reciprocating grate, 0.1 and0.2 mn

3/s (0.12 and 0.23 m/s at 298 K). At the secondhighest moisture content, 40.3% (curve C), the reactionfront propagates slightly outside of the calculated limitof the airflow and the measurements themselves show acertain scatter. However, calculation and measurementsagree sufficiently well to explain the influence of moist-ure; the fuel had to be dried to allow the desired airvelocities. The calculation shows that it is possible toachieve two stable velocities of the reaction front at thesame airflow. The change of velocity observed, the“scatter” (C in Figs. 8 and 10) could be a consequenceof a transition of the velocity from one of the stablevelocities to the other.

7. Conclusions from measurements

As mentioned above, it is generally assumed that ignitiontakes place on the surface of the bed and that the reactionfront propagates down through the bed in a cross-flow situa-tion, such as in Fig. 2(a). The measurements show, however,that for the boiler concerned this cannot be the case:

1. In the pot furnaces the reaction front could not propagatethrough the bed for the same type of fuel and airflows asin the boiler, where the fuel burned without problems.

This observation is supported by the model calculations.2. Even the highest velocity of the reaction front, 0.35 mm/

s, measured for wood cubes with a moisture content of10%, is not sufficient for the front to reach the surface ofthe reciprocating grate within the first 4 m, if the bed isignited from the top. For a bed height of 500 mm, itwould take 1430 s for the reaction front to propagatefrom the surface of the bed to the grate. With the velocityof the grate of 6 mm/s, the reaction front would reach thegrate 8.6 m after ignition on the surface. The correspond-ing distance at velocities measured for wet fuels is 18–60 m. In contrast, in the boiler case, according to Figs. 5and 6, the high temperatures clearly indicate thatcombustion takes place at or close to the surface of thegrate after less than 1.8 m.

3. The temperature on the grate, Fig. 5, shows that heat wasgenerated in the bed before ignition was visuallyobserved on the surface of the bed.

4. There was a heavy evolution of smoke from the bedbefore the position of ignition on the surface of the bedand before the visible flame zone, according to visualobservations in the reciprocating grate furnace.

5. Volatiles were found far from the fuel inlet, Fig. 6. Amoist wood-chip particle (50% moisture) dries and devo-latilises completely in two minutes at a temperature of973 K [15]. The temperature inside the bed is around1300 K [2,14] during char combustion, and the actualtime for complete drying and devolatilisation should beless than 2 min. The fuel is transported 0.7 m along thegrate in 2 min. Ignition is measured within the first 1.8 mfor pure wood chips on the reciprocating grate, Fig. 5,and all moisture and volatiles should have left the bedbefore 2.5 m (1.81 0.7 m) distance from the feed point ifthe reaction had propagated from the top of the bed to thegrate. However, Fig. 6 shows that volatiles leave the bedup to 4–5 m from the beginning of the grate.

The conclusion from these facts is that the ignition has nottaken place on the surface of the bed, but in the bed, mostlikely on the surface of the grate. The arguments supportingthis observation and that reaction propagates up through thebed, Fig. 2(b), are:

1. In such a case, the theoretical maximum moisture contentis attained when the lower heating value for moist fuel isequal to zero. This occurs at a moisture content of 85–90%, excluding heat losses. The reaction takes placeinside the bed in a location which is quite well insulatedfrom the surrounding. A moisture content of up to 70 or80% should therefore generate sufficient heat for dryingand devolatilisation. The heat is generated at the bottomof the bed by char combustion and is transported upthrough the bed by the gas, which dries and devola-tilises fresh fuel. For a counter-current bed, which isignited from the top, on the other hand, this moisturecontent is too high, since in this case, devolatilisation


and combustion takes place in a narrow front. Thecalculation shows that the maximum moisture contentin the range of airflows considered is between 35 and45%. It is also clear from the calculation that thevelocity of the reaction front becomes very slowfor these moisture contents.

2. Combustion and heat release in the bottom part of the bedgenerates gas, which transfers its heat to the fresh fuel andexits the bed at a temperature not much higher than that ofentering fuel particles. This explains the heavy evolutionof smoke, observed to leave the first 1–1.5 m of the bed.

3. The reaction front propagates up through the bed and thedevolatilisation continues until the devolatilisation frontreaches the surface of the bed. This explains the volatilerelease far down on the grate, see Fig. 2.

4. Ignition of the fuel on the surface of the grate takes placeas soon as the fuel has reached the ignition temperature.Larger particles need longer time to heat up and ignite, andconsequently there is a later ignition of the pure woodchips than of the forest waste that includes a large portionof fine saw-dust, although the moisture content was 10%higher, Fig. 5.

Large scale mixing of the fuel bed could be another reason forthe temperature raise before 1.8 m from the fuel inlet, butignition or stirring caused by the transport of the bed alongthe grate were not observed on the surface during the first 1–1.5 m from the fuel inlet. Another fact that is against largescale mixing is the tendency of wood chips to stick together.

8. How can the fuel ignite on the grate?

There are at least two mechanisms that can explain asteady state ignition of the bed at the surface of the grate:

1. burning char particles that are not transported along thegrate by the reciprocating rods;

2. conduction of heat through the metal rods.

It is nearly impossible to extinguish a burning charparticle by an airflow containing oxygen. The most probablereason for ignition of the bed is by such burning particles.The initiation of combustion on the grate is achieved by theignition of a pile of wood chips soaked in diesel oil. Theburning pile heats up the furnace and the metal rods. The fuelis then slowly fed and is ignited by the burning pile. Morefuel is introduced until a stable operating condition isattained. The steps of the reciprocating grate provide placesfor small burning char particles to stay, and they are alwayssupplied by oxygen from the primary air. These particlesignite the fuel above them and heat up the metal rods andnew fuel particles are heated by backward transportation ofheat through the metal rods. New char particles replace theold ones as they burn out or are transported away, and so asteady state ignition procedure is maintained.

9. Conclusions

The traditional description of the combustion behaviour,with ignition on the top of the bed and a reaction frontpropagating down through the bed, Fig. 2(a), was notobserved on the reciprocating grate studied. As the fuelmoisture content raises, the reaction front will have greaterdifficulties to propagate from the surface of the bed down tothe surface of the grate. The possibility for the reaction frontto propagate depends on the airflow and the fuel’s moisturecontent. In the reciprocating grate studied the airflows were0.1 and 0.2 mn

3/s, and for these airflows the limiting moisturecontent is between 35 and 45% according to calculation.This conclusion is also supported by pot furnace experi-ments. Both calculation and measurements show that thevelocity of the reaction front is very slow for fuel havinghigh moisture content.

A combustion behaviour, that explains the measurementsand allows fuel with a high moisture content to burn, takesplace if the reaction front moves in the same direction as theprimary airflow, Fig. 2(b). In such a case the bed has to beignited close to the surface of the grate. The char combus-tion produces hot gases, providing heat for drying anddevolatilisation on their way up through the bed. Thiscombustion situation should not be sensitive to disturbancesin airflow and moisture content of the fuel due to the stabi-lity of the char combustion. It becomes more similar to acounter-current bed than to the traditional description of across-current unit. The cross-current combustion of wet fuelshould be described by a fuel batch ignited from the sidewhere the primary air is introduced and not from oppositeside as is traditionally assumed. If this is the actual combus-tion behaviour, it will have a great influence on the princi-ples for boiler design. The ignition refractory arch is notneeded for ignition. Instead, shape, position and movementof the metal rods of the grate control where and when igni-tion takes place. Further experiments in reciprocating gratefurnaces and in pot furnaces are needed to finally concludeif this is the typical combustion behaviour of wet biofuel,but the circumstantial evidence presented gives a strongindication that this is the case.

A general conclusion from this work is that, if it is possi-ble to create a steady state ignition at or close to the surfaceof the grate, the reaction front always propagates from thegrate up to the surface of the bed. There are locations forburning char particles that can ignite the bed at or close tothe grate surface in all designs of travelling grates and thereciprocating grate is not a special case.

Acknowledgements

This work was supported by a grant from the Small ScaleCombustion Programme of the Swedish National EnergyAdministration. Part of the work was carried out under theEuropean Union contract JOR3-CT96-0059.


Appendix A

The adiabatic temperature for different air ratios isestimated by

H ZTad

T0

Xi

niCp;i dT Cp;i ai 1 biT

)X

i

nibi =2

!T2

ad 1X

i

niai

!Tad

2 H 1X

i

nibi =2

!T2

0 1X

i

niai

!T0

! 0 A1

wheren is the number of moles of speciesi, Cp the specificheat,T the temperature andH the heating value of wet fuelper kilogram dry fuel:

H Hu 2 HvapXm=1 2 Xm A2whereHu is the lower heating value of dry fuel,Hvap the heatof vaporisation andXm=1 2 Xm the moisture content basedon dry fuel. The number of moles of each species is calcu-lated from the assumption that the char is pure carbon andthe volatiles consist of methane, water, carbon monoxide,carbon dioxide and that the devolatilisation is thermallyneutral. The number of moles of each specie as a functionof air-to-fuel ratiol can be expressed as:

nN2 l3:77nC;c 1 2nCH4;v 1 0:5nCO;v

l $ 1

nO2 l 2 1nC;c 1 2nCH4;v 1 0:5nCO;v

nC 0

nCO2 nCO2;v 1 nC;v 1 nCH4;v 1 nCO;v

nCO 0

nCH4 0

nH2O nH2O;w 1 nH2O;v 1 2nCH4;v

l , 1

nO2 0

nC 1 2 lnC;c

nCO2 nCO2;v 1 lnC 1 nCH4;v

nCO 1 2 lnCO;v

nCH4 1 2 lnCH4;v

nH2O nH2O;w 1 nH2O;v 1 2lnCH4;v

A3

Number of moles in the moisture is:

nH2O;w Xm=1 2 XmMH2O: A4Number of moles in the char is:

nC;c Ychar=MC A5whereY is the mass fraction in dry fuel andM the molarmass. The molar composition of the volatiles is given by the

system of equation:

YC 2 Ychar=MC nCH4;v 1 nCO;v 1 nCO2;v;

YO2=MO2

nCO2;v 1 0:5nCO;v 1 nH2O;v;YH2

=MH2 2nCH4;v 1 nH2O;v;

Hu nC;chC 1 hO22 hCO2

1nCH4;vhCH4

1 hO22 hCO2

2 2hH2O1nCO;vhCO 1 hO2

2 hCO2

A6

whereh is the enthalpy at reference temperature.

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Paper VIII

Progress in Thermochemical Biomass Conversion 17-22 September, 2000, Tyrol, Austria

Combustion processes in a biomass fuel bed - Experimental results

Marie Rönnbäck, Monica Axell, Lennart Gustavsson SP Swedish National Testing and Research Institute,

BOX 857, SE-501 15 Borås, Sweden Henrik Thunman, Bo Leckner

Chalmers University of Technology, Energy Conversion, SE-412 96 Göteborg, Sweden

ABSTRACT: Combustion processes in a biomass bed are investigated experimentally. Special attention is paid to the influence of primary airflow and particle properties on the ignition front, its temperature and on the composition of the gas leaving the front. Two test rigs have been built: a large rig in the same size as a boiler for domestic use and a small laboratory test rig. In both rigs the ignition front moves in opposite direc-tion to the primary airflow. Three combustion regimes are identified: a sub-stoichio-metric regime with incomplete consumption of oxygen, a sub-stoichiometric regime with complete consumption of oxygen and an over-stoichiometric regime. The results show that a fuel with higher density and thermal conductivity (but in other respects similar to other fuels) has a wider sub-stoichiometric regime where oxygen is com-pletely consumed. If the particle size is increased (for the same fuel quality) the airflow range of this regime becomes shorter and starts at higher airflow. INTRODUCTION Fixed or moving bed combustion is the most common technology for biofuels. Incin-eration of wastes and gasification of biomass are also often performed in a bed. The design of the grate (stationary, vibrating, reciprocating or moving) on which the bed rests and the method of fuel supply (from underneath, from the side or from above) depend on fuel characteristics and on the size of the plant. Devices with bed combus-tion have as common features drying, devolatilization, gasification and combustion occurring in particular zones in the bed. The extension of these zones depends on fuel and air supply and on the initial ignition of the fuel bed. The bed may be operated as a gasifier producing a combustible gas, but it may also be operated with excess air. The purpose of a boiler is to attain complete combustion, although this is achieved down-stream of the bed in the form of gas phase combustion controlled by secondary air. For fuels with a high content of volatile matter, the gas combustion downstream of the bed is crucial for emission control. The fuel bed is the first stage in the combustion process and generates the conditions for the latter part. A review of available literature on the experimental simulation of solid fuels confirms that the knowledge of coal com-bustion is more detailed than that of biomass and municipal solid waste. The knowl-edge of biomass gasification devices today is extensive; however, see for example La


Fontaine and Reed (1) and this knowledge also suits the combustion bed. Also, recently several publications have described experiments on high volatile fuels in one-dimensional batch-type reactors. The fuel beds are ignited on the top and the ignition front propagates against the primary airflow. The results from such experiments can be extended to steady-state combustion on a stationary or moving grate. Gort (2) did a thorough investigation on the effects of moisture and volatile content, as well as of particle size. He burned wood cubes, coke and municipal solid wastes in a batch-type laboratory grate furnace. He distinguished three global reaction regimes, depending on the ratio of ignition rate and superficial air velocity. Shin and Choi (3) studied the effects of air supply rate, fuel particle size and calorific value on the com-bustion of wood cubes in a similar combustor. Depending on the availability of oxygen, distinct reaction zones were identified. Fatehi and Kaviany (4) performed similar ex-periments in a 7x7-cm² furnace on wood spheres and described two combustion zones. Furthermore, Kuo et al. (5) pointed out the importance of the arrangement of air supply for combustion efficiency. In their experimental device primary air could be supplied through the grate and through the walls of the fuel chamber. They found that the CO-emissions were related to the oxygen content of the flue gas, depending on the mixing of gas and air in the bed. Horttanainen et al. (6) presented results from experi-ments on biomass particles of various sizes and moisture content. They focused on the speed of the ignition front as an important factor determining the release of volatiles and that affects the combustion power and the stability of combustion. The aim of the present work is to further analyse the influence of primary airflow and fuel particle parameters on the combustion process. The work ranges from sub-stoichiometric to over-stoichiometric supply of primary air to the bed, to cover the influence of the parameters studied. Experiments were performed with the combustion front moving both upward (as in the studies referred to) and downward (as in a modern boiler with down-draught combustion). The work aims at forming a basis for modelling of wood burning, as well as for design of small boilers. The experiments were con-ducted so that the results can be used for both batch and continuously fired plants. EXPERIMENTAL CONDITIONS The experiments were carried out in two test rigs, here called the large and the small rig. The small rig is cylindrical with a diameter of 0.2 m and a height of 0.6 m. The inner wall is made of 3-mm stainless steel to minimise the heat capacity of the wall. It is insulated with a 50-mm glass-wool cover. Primary air is supplied through the steel grate at the bottom of the cylinder and exhaust gases leave through the top, where sec-ondary air is supplied before the gases enter the chimney. The fuel is put on the grate and ignited by a torch from the top. Then, the ignition front moves against the primary airflow towards the grate, see Figure 1. This is a one-dimensional representation of a continuously burning fuel bed on a grate, where fuel and air are supplied co-currently and the fuel is ignited on the top of the bed, see e.g. Thunman and Leckner (7). Two thermocouples (type K) located 150 mm and 300 mm above the grate measure the temperatures inside and above the fuel bed. Gas analysis is carried out in the gases leaving the bed, before they reach the secondary air supply. The large rig is of the same size as a domestic boiler. The design is chosen to ensure well-defined start- and boundary conditions for the fuel bed. The rig is equipped to measure airflow, weight loss and bed height. Temperatures can be measured upstream, in and downstream of the fuel bed and in the grate by shielded 1-mm thermocouples (type K), mounted both from the side (orthogonal to the movement of the ignition


front) and from the air supply. A comparison with shielded 2- and 3-mm thermocou-ples showed that the mounting of the thermocouples and their sizes gave no significant differences in results. The fuel bed can be observed through sight glasses. The rig works with down-draught combustion, i.e. the primary air is supplied from the top of the fuel bed and the fuel is ignited from the bottom (in this case by electrical spirals in the grate). The ignition front moves against the primary airflow towards the top of the fuel bed, see Figure 2. The fresh fuel moves downwards into the ignition front and influences the ignition front with its weight.

Figure 1 Ignition front moving against the airflow in the small experimental rig.

Figure 2 Ignition front moving against the airflow in the large experimental rig.

The fuels were pellets and wood cylinders (pine). The pellets were made of com-pressed sawdust and had a diameter of 8 mm. The wood cylinders had three diameters, 8, 12 and 34 mm. The proximate analyses and elemental composition of the fuels were almost identical, as seen in Table 1. The density and the thermal conductivity of the pellets are about twice those of the wood. The pellets were burned both in the large and in the small rig, while the wood cylinders were burned only in the small one. Table 1 Fuel characteristics.

Pellet

Wood

C (weight-%, dry basis) 50.5 51.4 H (weight-%, dry basis) 6.2 6.7 O (weight-%, dry basis) 43.1 41.7 N (weight-%, dry basis) 0.15 0.047 S (weight-%, dry basis) 0 0 Moisture (weight-%) 8.3 9.1 Hi (MJ/kg, dry basis) 20.2 19.3 Thermal conductivity (J/mK) (8) 0.32 0.16 Diameter (mm) 8 8 12 34 Fuel density (kg/m3) 1259 579 585 581 Bed density (kg/m3) 680 307 305 279 Bed void 0.46 0.47 0.48 0.52 Air mass flow (kg/m²s) 0.035-0.41 0.07-0.53 0.07-0.53 0.07-0.53


Emissions of CO, CO2, O2 and THC (Total Hydro Carbon) were measured on-line. The gas was sampled as close to the fuel bed as practically possible. In the large rig, gas was extracted 50 mm downstream of the grate. The distance to the ignition front is then 100-350 mm, increasing as the ignition front moves upward in the fuel bed. In the small rig, gas was extracted in a position 450 mm above the grate. The distance to the ignition front is then up to 450 mm. The gas probe is cooled to quickly stop any com-bustion reaction, and the temperature of the extracted gas falls to 100°C in less than 200 mm. Because of the high levels of CO downstream of the fuel bed, a dilution de-vise was used to dilute the sampled gases about 10 times. A conventional instrument could then measure the CO-concentration. The dilution factor was continuously calcu-lated by comparing the CO2-concentration before and after dilution. RESULTS AND DISCUSSION The ignition rate of the fuel bed is defined as kg ignited fuel per grate area and time (kg/m²s). In the small rig this quantity was determined by the times when two thermo-couples at a distance of 150 mm reached 500°C, multiplied by the (original) bed den-sity of the fuel. The exact level of temperature chosen (500°C) is not critical, because the temperature change in a fuel layer is quite fast, see Figure 3. The primary air mass flow through the grate is presented as kg air per grate area and time (kg/m²s). Figure 3 shows the temperature at 150 mm and at 300 mm above the grate. The short peak in temperature is the front temperature, most likely influenced by the surface temperature of the nearby particles. In this example the air mass flow is low, and all fuel is not converted but accumulates upstream of the ignition front. The temperature in the partly converted layer is about 100°C lower than in the front. As the bed shrinks the upper thermocouple finds itself above the bed. Because of radiative cooling by the walls the uncorrected temperature is about 200°C lower than the bed temperature.

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Figure 3 Temperatures at 150 mm and 300 mm above the grate and airflow in the small rig. The fuel was 8-mm wood cylinders and the air mass flow 0.11 kg/m²s. The temperature curves show how the width of the accumulated layer broadens as the front moves downwards. When the ignition front reaches the grate, there is a peak in temperature (at about 43 minutes) caused by combustion of the accumulated char.


As can be seen from the gas analysis in Figure 4 there is also a peak in CO- and a dip in CO2 –emissions followed by a peak in CO2 while CO goes to zero. The peak in CO coincides with a dip in temperature. When char combustion starts the production of water vapour from drying and combustion falls and the CO-emission increases because of lack of water vapour for CO-oxidation as illustrated by the expression: -d[CO]/dt = ko[CO][O2]

1/2[H2O] 1/2exp(-E/RT) from Howard (9). The final increase in CO2 follows from an increase in O2-concentration, enhancing combustion, when the bed is almost finished and very shallow. This dip-and-peak behaviour is not seen at high air mass flows (above 0.17 kg/m²s for wood cylinders and above 0.40 kg/m²s for pellets).

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Figure 4 Emissions of O2, C O2, CO and THC downstream of the grate in the small rig. Data as in Figure 3. The peaks in O2 with corresponding dips in CO2, CO and THC originate from back-blowing the analysis system. In the large rig electrical heating of the grate ignites the fuel. The ignition front moves upward, opposite to the direction of the airflow. The temperature profiles are steep and parallel during the devolatilization. Figure 5 shows temperatures at different levels in the centre of the bed between 10 mm and 400 mm above the grate. Two phases, devolatilization (ca 125-180 min) and char combustion (after 180 min) are indicated by the temperature curves and by the gas analysis downstream of the grate. Figure 6 shows the gas analysis from the same experiment. After bed break-through the bed consists mainly of char and the fuel burns from the top downwards. The tempera-ture in the top layer, where the air meets the fuel, shows peaks to maximum 1100°C. The temperature increases continuously in the remaining bed during char combustion. In this rig, the ignition rate of fresh fuel cannot be determined in the same manner as in the small rig, because the bed shrinks during conversion of the fuel. Instead, the time between the moment when the gas downstream of the bed reaches 500°C and when the ignition front breaks through the top of the fuel bed was measured. The ignition rate in kg/m²s is calculated by dividing the mass of the fuel in the bed by the grate area and the corresponding time. The break-through of the ignition front at the surface of the bed can be determined in several ways: visual observation of flames above the bed, a rise in temperature in the topmost fuel layer and changes in the gas analysis. In the ignition front there is a balance between heat generated by chemical reactions and heat transfer into the fuel particles, to the combustion air and to new layers of fresh


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Figure 5 Temperatures in °C at levels above the grate from 10 mm to 400 mm in the large rig. The air mass flow was 0.12 kg/m²s and the fuel 8-mm pellets.

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Figure 6 Emissions of O2, CO2 and CO downstream of the grate in the large rig. Data as in Figure 5. The peaks in O2 with corresponding dips in CO2, CO and THC originate from back-blowing the gas analysis system. fuel. The heat transport to new fuel is dominated by radiation, because the direction is opposite to the airflow. The heat transport into the fuel particles depends on the thermal conductivity of the material. The particles used were all thermally thick, i.e. the Biot number = hDp /k > 1, and a temperature gradient was present in the particles during devolatilization and char combustion. As a particle is heated, it dries and devolatilizes. Water vapour and combustible gases are produced and transported to the surface of the particle and out into the gas between the particles, where the gases ignite if the conditions are suitable. Devolatiliza-tion of biomass starts already at temperatures about 200°C and spontaneous ignition of


wood at 500-600°C. If a pilot flame is present, such as the flame front in a fuel bed, ignition can take place already at 300-400°C, Saastamoinen et al. (10). When the volatile matter has left the particles, heterogeneous reactions, such as gasi-fication with CO2 and H2O and char combustion, begin. Char combustion is a slower process than gas combustion and demands a higher temperature (≥ 800°C) to be com-plete. As long as oxygen is present combustion dominates, since gasification is slow. COMBUSTION REGIMES Figure 7 shows the maximum temperatures and Figure 8 the ignition rates in the small rig with 8-mm wood cylinders and 8-mm pellets as fuel. The lines in Figure 8 represent the theoretical stoichiometric combustion rate that would occur if the fuel was exposed immediately to oxygen, i.e. if the fuel particles were thermally infinitely thin.

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Figure 7 Maximum front temperature for 8-mm wood cylinders and 8-mm pellets as function of air mass flow rate. The sub-stoichiometric regimes with complete oxygen consumption for the different fuels are marked in the figure. Based on the results, the combustion process has been divided into three regimes. (1) Sub-stoichiometric combustion with incomplete consumption of oxygen. This

regime is found at low primary airflow and is characterised by a clear division in time in a devolatilization phase followed by char combustion. During the devola-tilization, partly converted fuel accumulates downstream of the ignition front. De-spite the sub-stoichiometric condition, oxygen is not fully consumed in the bed, ei-ther because of slow kinetics or of insufficient mixing between the devolatilized combustible gases and the primary air. As a result, just after the bed where the gas sampling was made, unburned gases as well as oxygen can appear in the sampling gas. The ignition rate and the ignition front temperature are strongly influenced by the primary airflow. Figure 3 and Figure 4 show combustion in this regime from 7 to 11 minutes.

(2) Sub-stoichiometric combustion with a complete consumption of oxygen. This regime occurs at higher primary airflow, see Figure 7 and Figure 9, and is charac-terised by complete consumption of oxygen in the bed. A layer of partly converted


fuel forms downstream of the ignition front, but the layer does not grow in thick-ness as in Regime 1. The devolatilization phase is followed by a short char com-bustion phase. The influence of primary airflow on ignition rate and ignition front temperature is not so pronounced. The maximum ignition rate and front tempera-ture are found in this regime. Figure 5 and Figure 6 show an example.


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Figure 8 Ignition rate for 8-mm wood cylinders and 8-mm pellets as function of air mass flow rate. The lines represent stoichiometric combustion. (3) If the primary airflow is increased even more the combustion moves into the over-

stoichiometric regime and excess oxygen leaves the fuel bed. As the excess air is heated, the bed cools. With increasing airflow the ignition rate slows down and the front temperature decreases. Finally, the combustion is extinguished. The final char combustion phase is negligibly short.

INFLUENCE OF DENSITY AND THERMAL CONDUCTIVITY The density and the thermal conductivity of the pellets are about twice those of the wood cylinders, but the fuels used differ very little in elemental composition and mois-ture content. In general, the differences in front temperatures and ignition rates are small for the fuels, as seen in Figures 7 and 8. The ignition rate of pellets is less influenced by air-flow in a wider range, and the temperature in the front is higher for pellets at higher airflows when for wood cylinders. The interesting difference lies in the combustion regimes. Pellets have a wider sub-stoichiometric, full oxygen consumption regime, starting at a lower airflow. At the temperatures and residence times during the change from Regime 1 to Regime 2, the conversion of CO, according to the rate expression of Howard (9), should be complete and no oxygen should be present. The reason for find-ing CO and O2 downstream of the bed is then most likely bad mixing. The pellets are thermally thinner than wood, and their higher thermal conductivity leads to a higher devolatilization rate at the same airflow. This may have contributed to extending the sub-stoichiometric regime with full oxygen consumption to higher air-flows in the case of pellets. The higher temperature in this regime (compared to wood) can be explained by a higher burning rate (kg mass loss/area and second) for pellets.


INFLUENCE OF PARTICLE SIZE Figure 9 shows the maximum temperature and Figure 10 the ignition rate in the small rig for 8-, 12- and 34-mm wood cylinders. No gas analysis was carried out on the 12- and 34-mm wood cylinder experiments and the temperature curves were used to sepa-rate the combustion regimes.


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Figure 9 Maximum front temperature for 8-, 12- and 34-mm wood cylinders as func-tion of air mass flow rate. The sub-stoichiometric combustion regimes with complete oxygen consumption for the different sizes are marked in the figure.


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Figure10 Ignition rate for 8-, 12- and 34-mm wood cylinders as function of air mass flow rate. The line represents stoichiometric combustion. At low airflow the front temperature is lower and the ignition rate appears to be somewhat higher for the largest fuel particles. However, the variations are generally


small and have to be compared with the accuracy of the experiments, especially for large particles whose size reduces the precision in the calculation of the ignition rate. The sub-stoichiometric regime with complete oxygen consumption starts at a higher airflow for the larger particles. This can be explained by the larger particle being ther-mally thicker. The resistance towards heat flow into the particles increases with the diameter. More of the heat produced is transported to new layers of fresh fuels and not towards the centre of the fuel particle. This is reflected in a higher ignition rate and a lower front temperature at low airflow. Less combustible gases reach the surface of the large particles, the power produced is lower and the burning rate also becomes lower. When the particle size increases the transition from Regime 2 to Regime 3 is ex-tended to higher airflow. The reason for this has to be further investigated. Parameters of interest are devolatilization rate compared to ignition rate, heat transfer between particles and primary airflow. COMPARISON BETWEEN THE TWO RIGS A comparison between ignition rates from 8-mm pellets burned in the small and in the large rig shows a reasonable agreement as seen in Figure 11. The front temperatures agree at low air mass flows, but at higher flows the temperatures in the large rig are lower, see Figure12. Four differences between the rigs can be noted: (1) The small rig has a smaller grate area and channelling inside the fuel bed is less

probable than in a large rig. In the large rig, horizontal temperatures were meas-ured in the bed and in the gas phase downstream of the bed. At several occasions an uneven start phase in the large rig resulted in an uneven ignition profile. An un-even ignition front could lead to a faster ignition of the bed, but the measured igni-tion rates are consistent and similar in the rigs (Figure 11). The method of measur-ing the ignition rate over the batch in the large rig is possibly removing any un-evenness in the ignition profile.

(2) In the small rig there is a risk for air passing between the outer edge of the fuel bed and the walls without taking part in the combustion process. In the large rig there is a seal between the grate and the walls, and any air and gas “channelling” be-tween the fuel bed and the walls is forced to move over the surface of the grate and leave through holes in the grate. This difference in design may lead to higher O2–levels downstream of the bed in the small rig.

(3) The large rig has a larger heat loss during batch firing, caused by the heavier de-sign. The ignition front, however, is well insulated by fresh fuel on one side and by partly converted fuel or char on the other, and there is only a heat loss at the walls.

(4) The most noticeable difference between the results from the two rigs is in the tem-perature of the reaction front (Figure12) at airflows higher than 0.3 kg/m²s when the temperature is 200°C higher in the small rig. Also the burning rate in the small rig is higher at these airflows. There are two explanations for the higher tempera-tures. The first is that in the small rig secondary air is supplied a few decimetres downstream of the bed, and the combustible gases leaving the bed burn with a gas flame that radiates upstream and heats the bed. At lower airflow the ignition front is covered by partly converted material and is not influenced by the heat from the flame. At higher airflow the layer of partly converted material is very thin and the front temperature increases by the heat from the flame. The second explanation is that in the combustion front of the small rig, particles with reduced size may start


to fluidise at high airflow, as shown in experiments of Fatehi and Kaviany (4), and that would increase the conversion rate and the temperature in the front.


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Figure12 Maximum front temperature for 8-mm pellets as function of air mass flow rate in the large and in the small test rigs. COMPARISON WITH OTHER AUTHORS Figure13 shows the maximum temperature in the small rig using 8-mm wood cylinders with a moisture content of 8.3 % compared to 10-mm wood cubes with a moisture content of 10 % from Gort (2). Figure14 shows the ignition rate of the same cylinders and cubes and of 5-20 mm wood chips with a moisture content of 10.8 % from Hort-tanainen et al. (6). The results coincide quite well, except for the higher ignition rate of


the wood chips. Horttanainen et al. suggest that smaller chips act as pilot flames for larger chips, and this enhances the ignition rate.


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Figure13 Maximum front temperature for 8-wood cylinders and 10-mm wood cubes as function of air mass flow rate.


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Figure14 Ignition rate for 8-mm wood cylinders, 10-mm wood cubes and 5-20-mm wood chips as function of air mass flow rate. Figure15 and Figure16 show the maximum temperature and the ignition rate in the small rig with 34-mm wood cylinders having a moisture content of 8.3 % compared to 30-mm wood cubes with a moisture content of 10 % from Gort (2). The results from the 34-mm wood cylinders are more scattered, probably because the cylinders form a less homogenous bed, which decreases the accuracy of the calculation of the ignition rates. Despite the scatter, the temperatures coincide well. For the larger particles (the cylinders) the maximum ignition rate is found at a higher air mass flow.


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Figure15 Maximum front temperature for 34-wood cylinders and 30-mm wood cubes as function of air mass flow rate.


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Figure16 Ignition rate for 34-wood cylinders and 30-mm wood cubes as function of air mass flow rate. Other authors have identified combustion regimes similar to this work. Gort (2) divides the combustion process into 1) a partial gasification regime characterised by accumulation of partly converted fuel and full oxygen consumption, 2) a complete gasification regime characterised by a layer of partly converted fuel with constant thickness and full oxygen consumption and 3) a complete combustion regime charac-terised by a layer of partly converted fuel with constant thickness and incomplete oxy-gen consumption. These regimes coincide in principle with the ones defined in the present paper with the exception that Gort found no excess oxygen after the bed in the first regime. Shin and Choi (3) identified three combustion modes depending on the air supply rate. When the air supply is low, the reaction rates are controlled by the oxygen supply


(oxygen-limited combustion). When the air supply increases, the flame propagation speed increases. However, the flame propagation speed is limited by the reaction rate of the fuel (reaction-limited combustion). When the air supply further increases, excess air cools the bed and puts an end to the flame (extinction by convection). Fatehi and Kaviany (4) identified in a similar way two modes and called them an oxygen-limited and a fuel-limited mode. None of these authors related the modes or zones to a descrip-tion of bed events. Nevertheless, the oxygen-limited mode should correspond to the sub-stoichiometric regimes, and the reaction- or fuel-limited one to the over-stoichiometric regime. CONCLUSIONS Two test rigs have been built for investigation of the combustion processes in a bed of solid fuels and particularly the influence of primary airflow and of particle properties (size, density and thermal conductivity) on the rate and temperature of the ignition front. Also the gas composition downstream of the bed has been investigated. The following conclusions can be drawn from the results: (1) The two test rigs show the same ignition rates, but the temperatures in the ignition

front diverge at higher airflow. This divergence may be caused by a difference in design of the secondary air supply, giving a higher heat transfer to the bed from the gas flame in the small rig. The higher temperatures may also be influenced by flu-idisation of particles in the front in the small rig, where the air is supplied from be-neath.

(2) Three combustion regimes were identified. At low airflow a sub-stoichiometric combustion regime with incomplete consumption of oxygen was found. This re-gime is characterised by a clear division in a devolatilization phase followed by a phase dominated by char combustion. During the devolatilization, partly converted fuel accumulates downstream of the ignition front. Although the combustion is sub-stoichiometric, oxygen is not fully consumed in the bed. At higher airflow there is a sub-stoichiometric combustion regime with a complete consumption of oxygen in the bed. A layer of partly converted fuel forms downstream of the igni-tion front, but it is not growing in thickness as in Regime 1. The devolatilization phase is followed by a short char combustion phase. When the primary airflow is increased even more, the combustion moves into the over-stoichiometric regime with excess oxygen leaving the fuel bed. The excess air cools the bed. At higher airflow the ignition rate slows down and the front temperature falls. Finally, the combustion is extinguished. In this regime, the final char combustion phase is neg-ligibly short.

(3) The two fuels compared show differences with respect to the combustion regimes. The thermally thinner fuel has a wider sub-stoichiometric, full oxygen consump-tion regime, starting at a lower airflow. Because of the higher devolatilization rate, the thermally thinner fuel has a sub-stoichiometric regime with full oxygen con-sumption sustained at higher airflow.

(4) Three sizes of the same fuel have been compared. At low airflow the ignition rate is higher and front temperature lower with the larger fuel. The resistance towards heat flow into the particles increases with diameter, and more of the heat produced is transported to new layers of fresh fuels and not towards the centre of the fuel particles. The larger particles are thermally thicker, and the devolatilization rate is lower. The sub-stoichiometric regime with complete oxygen consumption starts at


a higher airflow for larger diameter fuel, and the transition from Regime 2 to Re-gime 3 is extended to higher airflow. The reason for this has to be further investi-gated. Parameters of interest are devolatilization rate compared to the ignition rate and heat transfer between particles and primary airflow.

(5) In modern combustion equipment, the air supply is divided between primary air to the bed and secondary air to the produced gas. The primary air is kept sub-stoichiometric to enhance reduction of NO. The secondary air is important as a measure for mixing during gas phase combustion. This means that the most impor-tant regions for the primary air are the low velocity regimes. Knowledge of the in-fluence of fuel characteristics on the regimes is important for the division between primary and secondary air under various load conditions. However, depending on the design (e.g. batch-wise combustion or steady-state combustion on a transport-ing grate) the build-up of char or not is also an important issue to consider.

ACKNOWLEDGEMENT This work has been supported by the Swedish National Energy Administration, which is gratefully acknowledged. REFERENCES 1. La Fontaine, H. & Reed, T. B. (1993) An Inverted Downdraft Wood-Gas Stove and

Charcoal Producer, Energy from Biomass and Wastes XV, Washington D.C. 2. Gort, R. (1995) On The Propagation of a Reaction Front in a Packed Bed, Ph D

Thesis, Universiteit Twente, Enschede. 3. Shin, D. & Choi, S. (2000) The Combustion of Simulated Waste Particles in a Bed,

Combustion and Flame Vol. 121, pp. 167-180. 4. Fatehi, M. & Kaviany, M. (1994) Adiabatic Reverse Combustion in a Packed Bed,

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[8] Principles and Models of Solid Fuel Combustion

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