Universiteit Gent

Faculteit Ingenieurswetenschappen

Vakgroep Toegepaste Natuurkunde Voorzitter: Prof. dr. ir. C. LEYS

Modeling of heat and mass transfer in a reactor for plasma gasification using a hybrid gas-water torch

door

Stefaan JANSSENS

Promotor: Prof. dr. ir. G. VAN OOST Copromotor: doc. RNDr. M. HRABOVSKY

Scriptiebegeleider: Dr. Tanya Kavka

Scriptie ingediend tot het behalen van de academische graad van burgerlijk natuurkundig ingenieur

Academiejaar 2006-2007

Acknowledgement

Preparing this thesis I got my fair share of problems. Finishing this work would never have

been possible without the help of some persons whom I would like to thank. First my

promoters Guido Van Oost and Milan Hrabovský for giving me the opportunity to study this

interesting subject and for their support. Further I like to thank all the persons who helped

me at the IPP during my internship, including Tanya Kavka, Michal Hlína, Miloš Konrád,

Jiří Jeništa, Oleksiy Chumak, Alan Mašláni, Ivan Hirka, Vladimír Kopecký, Viktor Sember.

I should not forget to thank the users of the http://www.cfd-online.com forum, who helped

me answer questions and solve problems I encountered using the FLUENT software.

Special thanks go to my family and friends for the support they gave me the last 5 years

during good and bad times.

Stefaan Janssens, June 2007

i

Permission to give on loan

“De auteur geeft de toelating deze scriptie voor consultatie beschikbaar te stellen en delen

van de scriptie te kopiëren voor persoonlijk gebruik. Elk ander gebruik valt onder de

beperkingen van het auteursrecht, in het bijzonder met betrekking tot de verplichting de bron

uitdrukkelijk te vermelden bij het aanhalen van resultaten uit deze scriptie.”

“The author gives the permission to use this thesis for consultation and to copy parts of it for

personal use. Every other use is subject to the copyright laws, more specifically the source

must be extensively specified when using results from this thesis.”

© June 2007

Stefaan Janssens

ii

Modeling of heat and mass transfer in a reactor for plasma gasification using a hybrid gas-water torch

door

Stefaan JANSSENS

Scriptie ingediend tot het behalen van de academische graad van burgerlijk natuurkundig ingenieur Academiejaar 2006-2007 Promotor: Prof. dr. ir. G. VAN OOST Copromotor: doc. RNDr. M. HRABOVSKY Scriptiebegeleider: Dr. Tanya Kavka Faculteit Ingenieurswetenschappen Universiteit Gent Vakgroep Toegepaste Natuurkunde Voorzitter: Prof. dr. ir. C. LEYS

Summary Environmental issues and in particular waste management becomes more and more important in our society. Gasification and pyrolisis using plasma gives an alternative in addition to conventional waste treatment methods. This technology has potential in waste recycling, energy recuperation and also as a pre-treatment to landfilling. Since 2004 a plasma chemical reactor has been installed at the IPP-AS Prague, together with the academic partner Ghent University and the private partner Envitech S.A.. This experimental reactor uses a hybrid water-gas torch for the gasification of biomass. The aim of this thesis is to model using the CFD software FLUENT the physical processes acting in this reactor to obtain a better understanding. More in particular the mass and heat transfers were investigated. The first chapter gives an overview and an introduction to the subject. In the second chapter the used FLUENT model is explained in detail. The third chapter deals about how the input parameters for the model starting with experimental data were determined. In the fourth chapter the results of the simulations are shown and explained. The heat distribution and flow patterns are analyzed for different geometries of the plasma inlet. The behaviour of the jet in the reactor is compared with the one working in the open atmosphere and finally the influence of the dimensions of the inserted wood particles is examined. Chapter 5 deals with a total different topic. In this chapter some properties of a hybrid torch working in a vacuum chamber are investigated. Finally in chapter 6 a summary of the results is given and some recommendations are made how the simulations can be used to improve the design of the reactor. Key words: plasma chemical reactor, waste treatment, hybrid water-gas torch, FLUENT

iii

Modeling of heat and mass transfer in a reactor for plasma gasification using a hybrid gas-water torch

Stefaan Janssens

Supervisors: Guido Van Oost, Milan Hrabovsky, Tanya Kavka

Abstract� This article explains a 3D model using the CFD software FLUENT of a plasma chemical reactor used for waste treatment using a hybrid water-gas torch.

Keywords� waste treatment, plasma chemical reactor, FLUENT, hybrid torch

I. INTRODUCTION

Environmental issues and in particular waste management becomes more and more important in our society. Gasification and pyrolisis using plasma gives an alternative in addition to conventional waste treatment methods. This technology has potential in waste recycling, energy recuperation and also as a pre-treatment to landfilling, since plasma treatment of waste gives rise to some vitrified product and releases energy. Since 2004 a plasma chemical reactor has been installed at the IPP-AS Prague, together with the academic partners Ghent University and the private partner Envitech S.A.. This experimental reactor uses a hybrid water-gas torch for the gasification of biomass. In this abstract a 3D model of the current reactor using the CFD software FLUENT is discussed. Numerical simulations can lead to a better understanding of the different physical processes acting in this reactor. It is difficult to make observations, because of the extreme conditions acting in such a reactor. More in particular, the mass and heat transfers will be investigated.

II. EXPLANATION OF THE MODEL

A. Mesh Figure 1a shows the scheme of the reactor installed at the IPP.

Temperaturemeasurement

Windows

Gas sampling

Ceramic lining

Figure 1: a) scheme of the reactor b) 2D slice of the 3D mesh

At the top of the reactor biomass is inserted at a constant rate. It falls down under the influence of gravity and comes in contact with the plasma and is gasified. The produced gas consists mainly of H2 and CO (syngas) and leaves the reactor by the gas outlet. The reactor was translated into a 3D mesh using GAMBIT and exists of 600,000 tetrahedral cells and is shown in figure 1b.

B. Models For the calculations an Euler-Lagrangian approach was used. There was chosen for the RNG k-epsilon model and gravity and viscous heating are included. The particles will exchange momentum, energy and mass with the continuous phase from the moment they are inserted into the reactor.

C. Boundary conditions The heat losses to the walls are modeled by a constant heat flux out the reactor. The plasma is inserted at the top of the reactor using a velocity and temperature profile. At the anode located at the top of the reactor there is an extra volume momentum source added to model the interaction of the main jet with the anode jet. Close to this location there is also a heat source situated to simulate the Joule heating between the plasma inlet and the anode. The pressure at the gas outlet is the atmospheric pressure. At the waste input wood is inserted at a constant rate and in such a way that the temperature of the reactor is 1400K.

III. ACTUAL SIMULATION AND RESULTS

A. Temperature distribution of the inlet part The plasma inlet part, which is located between the anode chamber and the reactor, is a critical part in the reactor. The heat flux to this part can obtain very high values and has in the past caused a failure. For this purpose three different geometries have been simulated with exactly the same conditions. The temperature distributions of these parts are shown in figure 2. The three geometries have the same radius at the bottom, but the geometry in figure 2a is almost double as high as the others. It is clear that the distributions differ strongly. The maximum temperature of the geometries in figure 2a and 2b exceeds 10,000 K, while the maximum temperature for geometry c is less than 4000 K. In all the geometries the distribution is influenced by the deflection of

iv

the jet due to anode effects and thus one side is hotter than the other. The temperature is also strongly influenced by backflow of gas from the reactor to the anode. The geometry in figure 2c gives clearly the best results.

The jet in figure 4b gets attached to the wall and the initial deflection caused by the anode interaction increases. This is caused by the low pressure at the top left side in figure 3b. This deflection causes the wall temperature to be higher. In figure 4a this effect is not observed, because the pressure distribution is quite symmetric.

D. Particle tracking There were done simulations for three different particle sizes, to study the influence of the particle dimensions on the mass and heat transfer. In figure 5 the particle tracks colored by the size are shown for different initial particle diameters. The small particles will obtain fast heat and will evaporate quickly even before reaching the bottom of the reactor. The larger particles will evaporate everywhere in the reactor and a small fraction is even able to escape the reactor before being evaporated.

Figure 2: Distribution of the plasma inlet part for the three different geometries. (K)

B. Backflow of syngas The backflow of produced syngas from the reactor to the anode can damage the anode and has to be limited. This was tried by reducing the diameter at the top of the plasma inlet. Out the simulations we can conclude that this turns out not to work. Entrainment of gas in the jet creates a low pressure at the anode as can be observed in figure 3. Decreasing the diameter does not cause a reduction of this pressure and thus the backflow still exists. Changing the height of the inlet has a positive effect on the backflow, but has also some disadvantages. It increases the energy losses to the wall and decreases the velocity and turbulence in the reactor. Figure 5: Particle tracks colored by the particle diameter. The

initial particle size was between a) 0.1-0.5 mm b) 0.5-1.5 mm c) 1.5-3 mm

IV. CONCLUSION These simulations demonstrate that it is difficult to reduce the backflow to the anode chamber. It was showed that by choosing a proper geometry for the plasma inlet it is possible to reduce the heat losses. Simulations of more geometries should be done to find a perfect geometry that fulfills all requirements. Using such a model is can teach us a lot about the influence of the different parameters on the evaporation of the particles.

Figure 3: Distribution of the pressure. In figure a the pressure range is from -3000 Pa to 25 Pa, for b from -4000 to 25 Pa

C. Coanda effect The low pressure in the anode has also an effect on the deflection of the jet as can be seen in figure 4.

ACKNOWLEDGEMENTS

The authors would like to thank everybody who made it possible to study this subject.

REFERENCES [1] G. Van Oost, M. Hrabovsky, V. Kopecky, M. Konrad, M. Hlina, T.

Kavka, A. Chumak, E. Beeckman, J. Verstraeten, (2006). Pyrolysis of waste using a hybrid argon-water stabilized torch, Vacuum, 80, 1123-1137.

Figure 4: Distribution of the velocity. The velocity range goes from 0 till 3670 ms-1.

[2] FLUENT 6.2 users guide

v

Table of contents Acknowledgement i Toelating tot bruikleen ii Overview iii Extended abstract iv Table of contents vi Chapter 1: Introduction 1 1.1 Plasma 1 1.2 Treatment of waste 2 1.3 Experimental system at the IPP 3 1.4 Plasma torches 6

1.4.1 Gas stabilized torch 7 1.4.2 Water stabilized torch 8 1.4.2 Hybrid water-gas stabilized torch 8

1.5 Chemistry of the process 11 Chapter 2: Explanation of the model 15

2.1 Introduction 15

2.2 Mesh 15

2.3 Materials 19

2.4 Boundary conditions 19

2.4.1 Plasma inlet 19 2.4.2 Wood input 19

vi

2.4.3 Reactor walls 19 2.4.4 Gas outflow 20

2.5 Models 20 2.5.1 Euler-Lagrangian 20 2.5.2 RNG k-epsilon model 20 2.5.3 Gravity 21 2.5.4 Viscous heating 21 2.5.5 Mixing laws 21

2.6 Momentum exchange 22 2.7 Energy exchange 23 2.8 Mass exchange 24 2.9 Convergence criteria 25

Chapter 3: Calculation of the input parameters of the model 29

3.1 Power balance 29 3.2 Power balance reaction time 32 3.3 Temperature and velocity profiles 33 3.4 Volume heat source 37 3.5 Anode jet 39 3.6 Determination of the wood feeding rate 42

Chapter 4: Results of the simulation 44

4.1 Temperature distribution 44 4.1.1 Temperature distribution of the reactor walls 44 4.1.2 Temperature distribution in the reactor 45 4.1.3 Temperature distribution of the plasma inlet 47 4.2 Plasma jet characteristics 51 4.3 Anode influence 53 4.4 Coanda effect 54 4.5 Backflow of syngas 60

vii

4.6 Particle tracking 66

Chapter 5: Evaluation of the Ar flow rate of the hybrid low pressure torch 77

5.1 Mass spectrometer 77 5.2 Calibration 77 5.3 Argon flow rate 80

Chapter 6: Conclusion 86 Literature list 88

viii

Chapter 1: Introduction 1.1 Plasma Plasma is often referred to as the 4th state of matter. As temperature increases, molecules

become more energetic and transform in the sequence: solid, liquid, gas and plasma. In the

latter stages, molecules in the gas dissociate to form a gas of freely moving charged particles,

electrons and positive ions. This state is called the plasma state. On earth plasmas are rare,

but in the universe the majority of matter is plasma.

The most common way to generate and maintain plasma is by means of an electric discharge.

In such a discharge the high-mobility electrons pick up energy from the applied electric field

and then transfer part of this energy to the heavy particles through elastic collisions. The

electron temperature is set in such a way, that the energy received by electrons per unit time

transfers to heavy particles during the same period of time. But even with excellent

collisional coupling (high collision frequency) between electrons and heavy particles, there

will always be a difference between the electron temperature and the temperature of the

heavy species in the plasma. Only in the case of small values of E/p the temperature of

electrons and heavy particles approach to each other. This is a basic requirement for local

thermodynamic equilibrium (LTE). Additional conditions for LTE include excitation and

chemical equilibrium as well as certain limitations on the gradients in the plasma.

Complete Thermodynamic Equilibrium never exists in real plasmas. That is why a

classification of plasmas is based on the existence of LTE. Plasma that is in kinetic

equilibrium and simultaneously meets all LTE requirements is classified as thermal plasma.

[1], [4], [12]

- 1 -

1.2 Treatment of waste During the last ten years environmental issues have become more and more important.

Nowadays lots of waste is still being dumped or burned. Treatment of waste with plasma

technology offers a good alternative and is a more environmental friendly solution. It was

regarded for a long time as a too expensive solution because of the high energy cost of this

technology. With the continuous increasing importance of environmental aspects this

becomes less and less an issue. Plasma arc waste disposal is a method of waste management

which uses the extreme high temperature created by a plasma torch to break down organic

waste into gas used for power generation, and the inorganic fraction into hard solid rock-like

waste (slag) which can be used as a construction material. The process is intended to be a net

generator of electricity and to allow waste to be used completely, avoiding the need for

landfill. Investigations have been made to use this technology to treat industrial, military, and

medical wastes. Some facilities have already been build in Japan, Europe and the USA. The

first plasma based waste disposal system in the USA is scheduled to come into operation in

St. Lucie County, Florida. The county states that they hope to not only avoid further landfill,

but reprocess their historic landfills back to 1978 within 18 years as well. The plant is

scheduled to come into operation in 2008-09, and to produce 600 tons of solid rubble from

around 3000 tons of waste per day at around 5500 ºC. Some similar but smaller plants are

already in operation in Japan.

Plasma pyrolysis and gasification with the aim to produce syngas is an alternative to

conventional methods of biomass gasification. Plasma treatment offers some advantages

compared to the conventional methods of biomass treatment. It offers a better control of the

process temperature, higher process rates, lower reaction volumes and an optimum

composition of the produced gas. It exploits the thermo chemical properties of plasma. Not

only the particle kinetic energy in the form of heat is used for decomposing biomass, but also

the presence of charged and excited species makes the plasma environment highly reactive.

Another important advantage compared to the one of gases used in conventional methods is

the much higher enthalpy and temperature. Thus sufficient energy can be carried by a lower

flow rate and the composition of the syngas will be less affected.

- 2 -

Despite the big interest in the technology, there is still a lack of basic knowledge of the

physical and the chemical processes acting in the plasma reactors. Further there is little

known about the mass and heat balances in the fast changing conditions in the plasma

reactors. Because of the extreme conditions it is difficult to obtain information about the

chemical reactions and physical processes. There is a need of knowledge of the reactions

acting in the reacting to fully control the processes in the reactor.

[24], [20], [34]

1.3 Experimental system at the IPP To obtain more knowledge a research and development project has been started at IPP-AS

Prague, together with the academic partner Ghent University and the private partner Envitech

S.A.. At the IPP there is since 2004 a fully equiped plasma reactor operational. This reactor

uses a hybrid water-gas torch which was developed at the IPP. The experimental plasma

chemical reactor with closed water cooling system is designed to operate at 1700 °C and to

treat about 50 kg/h.

The experimental setup exists out of 5 principle units and is shown in figure 1.1. Namely a

feeder unit, the reactor, the plasma torch, a cooling unit and a combustion burner. The feeder

unit exists out of a hermetically closed container and a screw that regulates the feeding rate

of biomass. The pressure in this container is automatic adjusted in order that the pressure in

the material bin will always be higher than in the reactor to avoid leakages of gasses out of

the reactor. The waste container has a content of 30 kg. Until now the material used was

biomass (saw-dust) with different amounts of moisture. The feeding rate can be adjusted

from 10-95 kg h-1.

- 3 -

Figure 1.1: the experimental setup at the IPP

The reactor has an internal volume of 0.22 m3. To prevent power loss the reactor walls are

covered on the inside with different ceramic layers which can sustain high temperatures and

have a thickness of 400 mm. To prevent stresses in the ceramic isolation the reactor walls

have to be preheated slowly before an experiment with a gas burner till a temperature of

1100°C. The reactor is designed to work at wall temperatures of 1100°C-1400°C and a

feeding rate of 95kg h-1. All parts of the reactor are water cooled and with caloric

measurements of this cooling water the power losses can be measured.

At the top of the reactor the plasma torch is located and the jet is pointed down under a

certain angle. The material is inserted at the top of the reactor and falls under influence of

gravity down and encounters the plasma jet at about 30 cm downstream of the plasma

entrance. It is partially gasified during its flight within the jet; the non-gasified part of the

wood will fall to the bottom of the reactor where it will be gasified within the hot gas flow.

The exit tube for the syngas is located in the upper part of the reactor, in this way the

produced gases passes through the zone of high temperature within the plasma jet or close to

it. At three positions in the upper part of the reactor there are inputs for additional gases to

control the reactor atmosphere.

- 4 -

Temperaturemeasurement

Windows

Gas sampling

Ceramic lining

Figure 1.2: scheme of the reactor

The produced syngas leaves the reactor and is cooled down by a water spray in the quenching

chamber. The water flow rate is automatic adjusted so that the temperature of the gas is

around 300°C. After this the gas flows to the combustion chamber where it is combusted.

The energy produced in the reactor had to be destroyed in this installation for safety reasons.

In industrial operations this produced energy will of course be entirely recuperated.

- 5 -

Figure 1.3: photograph of the reactor

[6], [8], [10]

1.4 Plasma torches There exist many different types of Arc plasma torches. The principle differences are the

manner in which the arc is stabilized. The choice which torch to use depends of the plasma

properties needed for a specific application. As arc discharges are inherently unstable, the

torch will always need some stabilization mechanisms that keep the arc column in a given

stable position. Any accidental excursion of the arc from its equilibrium position causes an

interaction with the stabilizing mechanisms in such a way that the arc column is forced to

return to this equilibrium position. There exist different methods to stabilize the arc:

-free burning arcs, without external stabilization mechanisms

-wall stabilization

-conventional vertex stabilization

-magnetically stabilization

- 6 -

In case of the torches with wall or conventional vertex stabilization the stabilization

mechanism works by cooling down the arc column close to the wall. In case of the first, the

wall itself will cool down the column. By the conventional vertex stabilization a layer of

cold gas or water close to the wall will take care of this cooling. If the arc leaves the stable

position and arrives close to the wall, the arc column will be locally cooled. This will result

in a conductivity drop at this position as can be seen in figure 1.3 and the arc will be forced

back to his equilibrium position.

Figure 1.3: conductivity in function of the temperature

In more detail the gas stabilized, the water stabilized and the hybrid torch will be discussed.

[4], [20], [33]

1.4.1 Gas stabilized torch

The gas stabilized torches are the most common in the industry. The thermal plasma is

generated by an electric arc burning between the anode and the cathode. The most common

used gases are Argon, Nitrogen or a mixture of these with He or H2. The gas flow is also

used as the stabilization mechanism and as protection of the torch walls from overheating.

The plasma created by this type of torch has usually a temperature between 8000 K and

15000 K and an enthalpy between 1 and 100 MJ/kg. The plasma temperature and enthalpy is

- 7 -

limited by the fact that there is a minimum gas flow rate for every applied current due to the

function of the gas to protect the walls from overheating and the low enthalpy of these

gasses.

Figure 1.4: scheme of a gas stabilized torch

1.4.2 Water stabilized torch

In a water stabilized torch it is possible to create plasma with an extremely high plasma

enthalpy (150-300 MJ/kg) and velocity. In this type of torch, a liquid vortex is created in a

cylindrical chamber by a tangential injection of water. The electric arc is stabilized by the

water wall and the plasma is produced by the evaporation water of the vortex. The anode is

cylindrical and water cooled to reduce erosion.

Figure 1.5: water stabilized torch

1.4.3 Hybrid water-gas stabilized torch

This plasma torch which combines both principles of stabilization has been designed in IPP

in Prague. This is the type of torch used in the reactor for waste treatment. The arc column

is divided into two parts, an upstream gas stabilized part and a downstream water stabilized

part.

- 8 -

Figure 1.6: scheme and a photograph of the hybrid water-gas stabilized torch

The plasma jet properties such as velocity, enthalpy, mass flow rate, and others can be varied

in significantly wider range by changing the gas flow rate compared to pure gas- or liquid-

stabilized torches. It is possible to control the plasma velocity and momentum flux in the

plasma jet by changing the argon flow rate almost independently of the plasma temperature,

which is controlled by the arc current. This type of torch has some distinct characteristics:

• The plasma has a very high enthalpy (more than 200MJkg-1), till 30 times higher as

thermal plasmas created by other torches. By equal torch power the amount of

plasma gas is lower than by conventional gas torches. This results in the higher

enthalpy.

• High plasma temperature (more than 15000 K): A plasma temperature that is three

times higher than by other torches can be reached.

• High velocity and thus a high turbulence.

- 9 -

0 2 4mass flow rate [g/s]

60

50

100

150

200

pow

er [k

W]

Gas torches

Water torches

Hybridtorches

Figure 1.7: comparison of the different types of torches

The properties of this torch fulfill well the required ones for waste treatment. The low

amount of plasma gas will affect less the composition of the reaction products then by a

classical gas torch. To treat 1 kg waste, a gas torch uses 1 kg plasma; the hybrid torch only

needs 20-30g. In consequence using gas torches will have as affect that the reaction products

will contain a significant amount of N2 and O2 coming from the plasma gas.

The high velocity will result in an optimal mix and thus reaction between the treated material

and the plasma. The high temperature and intense amount of UV radiation will destroy most

complex molecules. It is expected that the produced syngas will not contain tar or other

dangerous chemical compounds. The extremely low plasma flow together with the high

plasma enthalpy will result in a high process efficiency and optimal composition of the

produced syngas. The next table gives an overview of some torches used for waste treatment

and their properties.

- 10 -

Table 1.1: Comparison of the enthalpy and temperature of torches used for waste treatment

Laboratory Type Power (kW) Plasma

Mean enthalpy (MJ/kg) Temperature (K)

IPP-CAS WSPH-500 150

water-

argon 225 15 000

IT RAS Novosibirsk EDP 217 150 steam 30 3 600

IT RAS Novosibirsk EDP 148 60 steam 60 4 500

Westinghouse MARC3 300 nitrogen 7 5 000

IPE RAS St. Petersburg EAG 6 250 nitrogen 16.7 6 300

Kobe Steel, Ltd. 300 nitrogen 17-34 6 300 - 7 500

[4], [5], [23], [33], [34]

1.5 Chemistry of the process

Gasification is the process by which either a solid or liquid carbonaceous material, containing

mostly chemically bound carbon, hydrogen, oxygen is reacted with air, oxygen and/or steam.

These reactions provide sufficient exothermic energy to produce a primary gaseous product

containing mostly CO, H2, CO2, H20 (g) and a small content of higher hydrocarbons. Heat

supplied by external sources to the reactor is used to control the process and the reaction

temperature, but most of the heat for realization of the reactor comes from the caloric value

of the biomass. In the case of thermal decomposition of biomass under the action of

externally supplied heat and without any oxidant, we speak of pyrolysis. Especially

pyrolysis is well adapted to the valorization of products as wood with good control of the

parameters of the process to maximize the production of syngas.

It is possible to distinguish three different types of reactions:

a) Pyrolysis with no oxygen added – syngas and small amount of solid carbon is produced

2 2 (O H C Owood n CO n H n n C⇒ + + − ) (1.1)

- 11 -

b) Gasification with addition of stechiometric amount of O2 – only syngas is produced

22( )

2O

C HnC nwood O n CO n H−

+ ⇒ + 2

2H

(1.2)

c) Gasification with stechiometric amount of CO2 – only syngas is produced

22( ) (2 )O c Owood nC n CO n n n H+ − ⇒ − + (1.3)

Where nC = c/MC, nH2 = h/2MH and nO = o/MO are the molar concentrations of carbon,

hydrogen and oxygen in wood. With the mass fractions of carbon, hydrogen and oxygen

equal to c, h and o, respectively. In the reactor with reaction temperature Tr, wood is

transferred into syngas (mixture of carbon monoxide and hydrogen) and solid carbon (in case

of pyrolysis). The heat for the reaction is supplied by plasma and is partially produced by

exothermic reaction of carbon oxidation (in case of gasification with oxygen addition). In

real experiments, also the hydrogen and the oxygen coming from the plasma participates in

the reaction with the amount determined by the ratio of the wood feed rate to the plasma flow

rate. This contribution of the plasma for higher feed rates is rather small and thus does not

influence much the calculated limits for maximum feed rates. As a chemical formula for

wood we can use C6H10O5.

Figure 1.8: a) energy consumption and b) the energy gain in function of the reaction

temperature

- 12 -

The energy consumption for the destruction of wood depends on the reaction temperature

and is given for the three processes a), b) and c) in figure 1.8 a. The energy gain is defined as

the ratio of the combustion heat of the generated syngas (ΔHc) to the total heat needed to

decompose wood into syngas (Δhr). The curves were calculated from values of Δhr for the

case of dry wood and wood with a water content of 10%. It can be seen how an addition of

oxygen leads to the combustion of a surplus of carbon and thus reduces the energy

consumption, while use of carbon dioxide as an oxidizing medium results in an increase of

needed energy. The energy consumption depends on the reaction temperature in the reactor.

This temperature is established by the adjustment of the relation between the plasma power,

the material feed rate and the power loss to the reactor walls.

The ratio of energy obtained by combustion of syngas ΔHc to the energy needed for its

production Δhr is plotted in figure 1.8 b against the reaction temperature for the three

described processes. The humidity of wood has also an effect on the pyrolisis. Especially

the gasification of dry wood with an addition of oxygen can lead to a higher energy gain of

the process.

There are two main factors determining the minimum reaction temperature needed for the

process. First, the temperature must be high enough to obtain an optimum composition of the

produced syngas. A calculated composition of the products formed by the gasification of

wood by a certain condition is shown in figure 1.9. It can be seen that the system is

decomposed mainly to hydrogen and carbon monoxide with a small amount of other

components at temperatures above 1200 K. This temperature is thus the limiting minimum

reaction temperature for obtaining syngas of a good quality.

- 13 -

Figure 1.9: the syngas composition in function of reaction temperature

The other lower limit for the reaction temperature follows out of the kinetics of the reactions,

which determine the total material throughput. The process of wood degradation is complex

and involves decomposition and depolymerization of wood components including

hemicellulose, cellulose and lignin with their individual kinetic rate constants. The kinetics of

chemical processes can be described by the classical Arrhenius equation. The activation

energy values in the Arrhenius equation for wood pyrolysis in nitrogen or air for

temperatures above 300 °C range from 96 to 227 kJ/mol. However, the kinetic parameters are

highly dependent on experimental conditions. For plasma pyrolysis the energy for wood

volatilization is almost completely supplied by the plasma rather than by chemical reaction.

The kinetics is thus strongly affected by the heat transfer rate to the wood surface. The heat

needed for volatilization of wood is transported to its surface through the produced gas

flowing from the surface into the volume. As the flow rate of the produced gas is one or two

orders higher than the plasma mass flow rate, the effect of the flowing gas on the heat

transfer is dominant. Also the composition of the atmosphere in the reactor and its

temperature is determined mostly by the gasified material.

[5], [8]

- 14 -

Chapter 2: Explanation of the model

2.1 Introduction

For the simulation of the reactor the CFD software FLUENT was used. The broad physical

modeling capabilities of FLUENT have been applied to industrial applications ranging from

air flow over an aircraft wing to combustion in a furnace, etc. The software code is based on

the finite volume method on a collocated grid. It is also possible to use in FLUENT MHD

equations. This was not done because it would only make a big difference close to the

plasma inlet and would cause a dramatic increase of the computation time. The model in

FLUENT was partially developed by Benjamin Defoort to obtain his PhD. The aim of the

CFD-model is a better understanding of the physical processes acting in the reactor and to

optimize the current reactor design. Due to the extreme conditions in the reactor, not all

processes acting in the reactor can be observed directly. For this reason a model will be

extremely useful to understand more about what is happening in the reactor.

Because the reactor is not totally axial symmetric a 3D model was chosen. This is the first

model to simulate plasma pyrolysis of biomass. Earlier there was developed by Ivan Hirka a

2D model without waste input. This model had limited physical applicability because of the

absence of axial symmetry. In the 3D model not all physical processes acting in the reactor

are yet included and there are still some uncertainties.

[9], [12]

2.2 Mesh

The 3D-mesh used was created using gambit. Gambit is a geometric modeling and grid

generation tool. It allows users to create their own geometry. It can automatically mesh

surfaces and volumes while allowing the user to control the mesh through the use of sizing

functions and boundary layer meshing. The fully detailed mesh exists out of more than 600,

- 15 -

000 tetrahedral cells. A graphical representation of a tetrahedral cell is shown in fig 2.1. It

exists out of 4 nodes, 6 edges and 4 faces.

Figure 2.1: graphical representation of a tetrahedral cell.

To obtain better results, the mesh was made finer where large gradients are expected. This is

for example the case at the plasma entrance and at the momentum source. This difference in

cell sizes was obtained using size functions. The next figures show 2D slices of the mesh.

The regions with smaller cell sizes are clearly visible.

Figure 2.2: 2D view of the mesh of the reactor colored by equisize skewness, lighter color

means less skewed.

- 16 -

Figure 2.3: Close up of the anode part

To evaluate the quality of the mesh we can use for tetrahedral elements the equisize skew.

This is defined as:

EQEVS

EQ

S SQ

S−

=

Where S is the volume of the mesh element and SEQ the maximum volume of an equilateral

cell with circumscribing radius which is identical to that of the mesh element. QEVS=0

describes an equilateral element and QEVS=1 a poorly shaped element. In general, high-

quality 3D meshes contain elements that possess average QEVS values of 0.4. The

distribution of the equisize skew is shown in figure 2.4 where the range goes from QEVS=0-1

with a division of 0.1. In this case that the majority of elements have QEVS values between

0.2 and 0.4.

- 17 -

Figure 2.4: Distribution of the QEVS values of the used mesh.

Figure 2.5 shows a close up of the top part of the reactor with the different parts indicated. In

the continuation these names will be used often. There were made 3 different geometries for

the plasma inlet part of the reactor as will be explained in chapter 4.

Figure 2.5: 3D close up of the top part of the reactor

[36]

- 18 -

2.3 Materials

The reactor exists out of aluminum. Wood is defined in the reactor as a combustion particle.

In FLUENT there should always be chosen an oxidizing medium. For this purpose Ar was

defined as “dummy” oxidizing medium, but without any Ar presented in the reactor. The

properties of the wood are defined as constants. The wood particles have a certain boiling

point and vaporization temperature. The combustible fraction is chosen almost zero and the

volatile fraction almost 1. The plasma and the syngas were modeled by respectively a fixed

mixture of H20-Ar and H2-CO. The properties of these gasses such as the density, thermal

conductivity, etc., are defined as temperature dependent polynomials.

2.4 Boundary conditions 2.4.1 Plasma inlet

The torch inlet at the top of the reactor is done by a 3D- temperature and velocity profile of

H20-Ar. The location is indicated in figure 2.5. The extra Joule heating between the exit of

the nozzle and the anode reattachment point is modeled by an extra constant volume heat

source. To describe the anode interaction a volume momentum source was added with

direction perpendicular on the main plasma jet. These volumes are shown in figure 2.3. In

chapter 3 there is explained in detail how the velocity profile, the momentum and heat source

are defined and calculated.

2.4.2 Wood input

At the top of the reactor wood particles are inserted at a constant rate. The wood falls than

under gravity in the reactor and comes in contact with the plasma jet where it is gasified.

How the feeding rate of wood is determined is also explained in more detail chapter 3.

2.4.3 Reactor walls

By caloric measurements of the cooling water the heat loss of the reactor was measured. A

spatial distribution of these losses is not known, but different parts of the reactor have in

reality different isolation. Heat losses to the walls are represented by a constant heat flux in

such a way that the total power losses equal 22 kW in total.

- 19 -

2.4.4 Gas outflow

The pressure at the gas outlet in the model is the atmospheric pressure. It is possible that

there occurs a reversed flow due to a localized lower pressure zone in the reactor close to the

gas outlet, because in the model the gas outlet was too short. In this case the reversed flow

exists out of a mixture of 10% H20-Ar and 90% H2-C0 at a temperature of 1400K.

2.5 Models

2.5.1 Euler-Lagrangian

The Lagrangian discrete phase model in FLUENT follows the Euler-Lagrange approach. The

fluid phase is treated as a continuum by solving the time-averaged Navier-Stokes equations,

while the dispersed phase is solved by tracking a large number of particles through the

calculated flow field. The dispersed phase can exchange momentum, mass, and energy with

the fluid phase. The particle trajectories (the wood particles) are computed individually at

specified intervals during the fluid phase calculation. Every 40th iteration of the fluid phase,

the trajectories of these particles are calculated.

2.5.2 RNG k-epsilon model

The RNG-based k-ε (with k the turbulence kinetic energy and ε its dissipation rate)

turbulence model is derived from the instantaneous Navier-Stokes equations, using a

mathematical technique called ”renormalization group” (RNG) methods. In the derivation of

the k- ε model it is assumed that the flow is fully turbulent, and the effects of molecular

viscosity are negligible. The standard k- ε model is therefore only valid for fully turbulent

flows. The RNG model yields a lower turbulent viscosity than the standard k-ε model. This

is the reason why the RNG model is been used instead of the standard model.

- 20 -

2.5.3 Gravity

Because the biomass falls under influence of gravity in the reactor, it has to be included in

the model. The reactor is tilted and thus the direction of the gravity force goes from the top

left to the right bottom, making a angle of 16.5° with the y-axis as shown in figure 2.2.

2.5.4 Viscous heating

Viscous dissipation describes the thermal energy created by viscous shear in the flow. In the

model viscous heating should be included because the shear stress in the fluid is large due to

the high velocities. In high speed turbulent flows the contribution of these terms in the

energy equation can be important.

2.5.5 Mixing laws

To describe the mixing of the plasma (H20-Ar) and the produced syngas (H2-C0) some

mixing laws have to be defined in FLUENT.

Density: the mixture is a non-ideal-gas mixture and thus the volume-weighted-mixing-law of

FLUENT is needed

1i

i

Yρ

ρ

=∑

(2.1)

Where Yi is the mass fraction and ρi the density of component i

Specific heat: in FLUENT mixing-law defined as:

,p i p ic Y c=∑ (2.2)

Thermal conductivity: This can be approximated by the mass-weighted-mixing law defined

in FLUENT as:

i i

j ij

X kkX φ

=∑∑ (2.3)

- 21 -

With

1 1,2 4

,1

2,

,

1 ( ) ( )

8(1 )

w ji

j w iij

w i

w j

MM

MM

μμ

φ

⎡ ⎤+⎢ ⎥

⎢⎣=⎡ ⎤

+⎢ ⎥⎢ ⎥⎣ ⎦

⎥⎦ (2.4)

With Xi de mole fraction, Mw,i the specific molecular weight and µi the viscosity of

component i.

Viscosity: the same approximation as for the thermal conductivity is made and thus the ideal-

gas-mixing law is used.

21 1,2

,1

2,

,

1 ( ) ( )

8(1 )

i i

j ij

w ji

j w iij

w i

w j

X µX

MM

MM

μφ

μμ

φ

=

⎡ ⎤+⎢

⎢ ⎥⎣ ⎦=⎡ ⎤

+⎢ ⎥⎢ ⎥⎣ ⎦

∑∑4 ⎥ (2.5)

2.6 Momentum exchange

There will be a momentum exchange between the solid and the continuum state in FLUENT.

The wood particles which fall under the gravity will get energy and momentum from the

plasma jet. FLUENT predicts the trajectory of a discrete phase particle by integrating the

force balance on this particle. This force balance equates the particle inertia with the forces

acting on the particle, and can be written as:

( )( )p

D pp

du gF u u

dtpρ ρρ−

= − + (2.6)

- 22 -

With up and ρp respectively the velocity and density of the particle, u and ρ the velocity and

density of the fluid.

The second term in the equation represents the acceleration due to the gravity and the first

term the acceleration produced by the drag force per unit particle mass.

2

18 Re24

DD

p p

CFd

μρ

= (2.7)

Where µ is the molecular viscosity of the fluid, dp the particle diameter, Re the relative

Reynolds number and CD the drag coefficient which depends on the geometry of the particle.

2.7 Energy exchange

In the reactor there will be an energy exchange between the plasma, the syngas and the wood

particles. In FLUENT the energy exchange between the particles and the gas will be

described by the following equations:

( )pp p c p dev

dT dmm C hA T T h

dt dt= − + p (2.8)

11322 0.6Re Prp

c

hdNu

k= = + (2.9)

Where mp is the particle mass, Cp the particle heat capacity, Tp the particle temperature, A

the surface of the particle, Tc the temperature of continuous phase, h the convective heat

transfer, hdev the heat of devolatization and kc the mass transfer coefficient, Nu the Nusselt

number, Re the Reynolds number and Pr the Prandtl number.

Equation 2.8 predicts the vaporization of a discrete phase particle and the change of

temperature of this particle. The particle temperature will be updated according to a heat

balance that relates the sensible heat change in the particle to the convective and latent heat

- 23 -

transfer between the particle and the continuous phase. The heat transfer coefficient, h, is

evaluated using the correlation of Ranz and Marshall. The heat of devolatilization of the

particles wood is calculated from the difference of the energy liberated by the combustion of

wood and the combustion of the products formed.

biomass dev productsh h hΔ = Δ + Δ (2.10)

2.8 Mass exchange

The kinetics of devolatilization of biomass is determined by Arrhenius equation. The

Arrhenius equation is a simple formula for the temperature dependence of a chemical

reaction rate. More correctly of a rate coefficient, as this coefficient includes all magnitudes

that affect reaction rate except for concentration. The Arrhenius equation is an expression

that shows the dependence of the rate constant k of chemical reactions on the temperature T

and activation energy Ea, as shown below:

exp( )aEk ART−

= (2.11)

Where A is the pre-exponential factor (defines the frequency) and R is the gas constant. In

diffusion limited reactions the pre-exponential factor will strongly depends on the

temperature and has to be estimated.

In the model the single kinetic rate model defined in FLUENT foor the mass exchange is

used. This devolatilization model assumes that the rate of devolatilization is first-order

dependent on the amount of volatiles remaining in the particle.

, 0 , 0[ (1 )pp v p

dm k m f mdt

− = − − ] (2.12)

- 24 -

Where mp is the particle mass, fv,0 the mass fraction of volatiles initially present in the

particle, mp,0 the initial particle mass and k the kinetic rate coefficient as defined in the

Arrhenius equation.

Figure 2.6: Mass and energy transfer between the wood particles and the surrounding gas.

In [8] a simple relation was determined for the characteristic time constants for the

volatilization rate controlled by the heat transfer to wood particles. This equation also gives

us the chance to estimate the factor A. The energy balance of volatilization is given by the

equation:

0 gasq m h= Δ& (2.13)

Where q0 is heat flux per unit surface from the gases in the reactor to the surface of the

particle, m is the mass flow rate of gas from a surface unit and Δhgas is the heat needed for

volatilization of a mass unit of material. The heat flux can be expressed as a function of the

gas flow rate using simple film theory for heat transfer between two phases at high mass

transfer rates.

- 25 -

0 /

( )( p

p r s

mC h

mC T Tqe

−=

−&

&1) (2.14)

Where Cp is the specific heat and h the heat transfer coefficient, both corresponding to local

conditions in the sheath of volatilized material around the particle, Tr and Ts are respectively

the temperatures in the reactor and the temperature on the surface of the particle. From

equation 2.13 and 2.14 we then obtain the following relation between temperature difference

(Tr -Ts) and gas mass flow rate:

ln( ( ) 1)pr s

p gas

Chm TC h

= −Δ

& T − (2.15)

Where h is evaluated using the same relation as in formula 2.9

Figure 2.7: calculated rates of volatilization for different particle surface temperatures Ts in

function of the particle temperature.

Figure 2.7 shows for different particle surface temperature the rates of volatilization. The rate

of volatilization increases with increasing temperature in the reactor. These curves can be

used to estimate the reaction temperature needed for a given flow rate and a given surface of

- 26 -

the material in the reactor. Using these curves it is also possible to estimate the pre-

exponential factor A.

Using figure 2.7 we obtain for Ts=1300K and Tp=1000K that a volatilization rate of 400 kgm-

2s-1. Ea lies typical between 96 and 227 kJ mol-1 and using these values and the equation

above we obtain A≈3.616 e8.

[3], [8], [12], [17], [35]

2.9 Convergence criteria

To control convergence of the solution the residuals where plotted and the total volume

integral of the temperature. The convergence criteria for the residuals were set to 1e-6. For

single precision computation, as used in these simulations, this is the maximum value.

The residuals should never be used as the only criteria to check convergence. Therefore the

total volume integral of the temperature was also evaluated. It is a sign of convergence when

the volume integral reaches more or less a constant value. In figure 2.8 and 2.9 an example

of the evolution of the residuals and the volume integral is shown. The fluctuations every

40th iteration are due to the discrete phase calculations which are only calculated every 40th

iteration, because otherwise it would influence too much the flow field calculations and

would lead to a longer computation time.

- 27 -

Figure 2.8: Evolution of the normalized scaled residuals

Figure 2.9: Evolution of the total volume integral of the temperature

[35]

- 28 -

Chapter 3: Calculation of the input

parameters of the model

3.1 Power balance The power inserted in the torch can easily be calculated by measuring the current and the

voltage till the exit of the nozzle. A part of the power inserted in the torch will be

transferred by radiation and conduction to the water cooled walls of the torch. By measuring

the temperature and the flow rate of the cooling water we can calculate with some easy

caloric measurements the heat losses using formula 3.1.

2lost p H OP C F= TΔ (3.1)

The cooling circuit exists of 4 different parts, cooling the anode, the cathode and the two

stabilizing chambers. The temperature and the flow rate to each of these parts can be

measured. Nevertheless there is a problem measuring the losses of the chambers separately,

because the two stabilization chambers are connected and thus the flow rate out of each

chamber is not known. Measuring these flow rates is not possible because the water contains

bubbles of argon that is pumped away together with the water. In the past there have been

some attempts to solve this problem, but without any result. Obviously the temperature can

be measured after mixing the cooling water of the two chambers. Consequently we know the

final temperature and the total flow rate of cooling water used to cool the chambers with

these data we can calculate the power losses of the chambers in total. The flow rate out of

the chambers will be a little bit smaller than the flow rate in because a small fraction of the

water will be evaporated and converted into plasma. However this amount is negligible for

the power balance calculations. The following figures represent de distribution of the losses

for different parameters and for the different parts of the torch. The loss at the cathode is

small because of the small size of the cathode spot. The water stabilizing chambers take

account for the biggest part of the losses and also the anode takes account for a large part of

the losses. Later this power balance will be used to calculate the velocity.

- 29 -

power loss Far=12.5 slm

I=230 AI=300 A

I=400 AI=500 A

cathode

anode

chamber

Figure 3.1: distribution of the power losses for different currents at an argon flow rate of 12.5

slm

power loss Far=22.5 slm

I=150 AI=230 AI=300 AI=400 AI=500 A

cathodeanodechamber

Figure 3.2: distribution of the power losses for different currents at an argon flow rate of 22.5

slm

From the graphs we can conclude that the distribution of the losses is almost independent of

the applied current.

- 30 -

The next graph represents the efficiency in function of the current. The full lines are the

efficiencies for the torch until the exit of the nozzle. The dotted lines represent the total

efficiency of the torch including the losses at the anode. If the current and thus the power

input or the argon flow rate increases, the efficiency will be higher.

Current - Efficiency

30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

100 200 300 400 500 600I (A)

%

Nozzle exit, F-Ar=22.5 slmNozzle exit, F-Ar=12.5 slmTotal, F-Ar=22.5 slmTotal, F-Ar=12.5 slm

Figure 3.3: The torch efficiency in function of the current

Current - Net power

0,0E+001,0E+042,0E+043,0E+044,0E+045,0E+046,0E+047,0E+048,0E+049,0E+04

100 200 300 400 500 600I (A)

Pow

er (W

)

P-nozle exit,F-Ar=22.5 slmP-nozle exit,F-Ar=12.5 slmP-total, F-Ar=22.5 slmP-total, F-Ar=12.5 slm

Figure 3.4: The torch net power in function of the current

- 31 -

From graph 3.4 we can conclude that the net power increases when the argon flow rate is

higher. The net power will increase when a higher current is applied.

[20]

3.2 Power balance reaction time

When measuring the power balance of the plasma torch, it is important to wait long enough

between two measurements with different torch parameters until equilibrium is reached. It

takes some time for the different parts of the torch to heat or cool down to the equilibrium

temperature. The following graphs are from a measurement of the plasma torch with an

argon flow rate of 22.5 slm and the current and thus also the power was subsequently

changed in the following order: 500A-400A-300A-230A-0A-150A. Out of graphs 3.5 and

3.6, the time needed to reach the steady state condition can be estimated. For the anode

cooling system this time is quite short and around 100s. The cooling system of the

stabilization chambers of the torch needs a lot longer to obtain equilibrium and at least some

minutes. The losses at the stabilization chambers are also fluctuating in time. For this reason

an average was taken to calculate the power balance.

Power loss - Time

0

10000

20000

30000

40000

5000 10000 15000 20000 25000Time (s)

Pow

er lo

sses

(W)

stabilization chamberanode

Figure 3.5: The measured power losses in function of the time

- 32 -

Power loss - Time

3000

8000

13000

18000

23000

12000 12250 12500 12750 13000 13250 13500 13750 14000Time (s)

Pow

er lo

sses

(W)

stabilization chamberanode

Figure 3.6: Close up of he measured power losses in function of the time

3.3 Temperature and velocity profiles

Measurements of thermal plasma jets are complex and difficult due to the extremely high

emitted light fluxes, very high temperature gradients, very high thermal fluxes and high

fluctuations of dissipated power. There are different types of diagnostic techniques. For

measurements close to the nozzle of the torch emission spectroscopy and laser scattering are

used. At the downstream part it is possible to use probe methods due to lower temperatures.

The different set ups for the measurements are shown in figure 3.7.

The temperature profiles used as input for the model were measured using optical emission

spectroscopy (OES). These measurements were done by Victor Sember. This technique

allows fast online measurements, but it is still important to be careful interpreting the results.

LTE is assumed to derive the temperature from the measurements of the excited population

level. This assumption is not correct close to the electrodes and will have as effect that the

temperature deduced from atomic lines will be overestimated. Another important

requirement is cylindrical symmetry.

- 33 -

Figure 3.7: Scheme of the measurements

The temperature profile at the exit of the torch can be measured by OES. From this profile it

is possible to deduce the velocity profile. We suppose that there is only a large pressure

gradient in the axial direction of the jet and that the pressure in the radial direction is almost

constant. The velocity in the radial direction is very small compared to the axial velocities.

Thus the Mach number can be assumed to be independent from the radial coordinates at the

exit of the torch. The Mach number is defined as

v(r) M=c(T(r)) (3.2)

Where c represents the sonic velocity which depends in the temperature and v the plasma

velocity.

The sonic velocity is given by the formula

pc= γρ (3.3)

The density ρ and γ are functions of the temperature and thus is the sonic velocity. We

assume that the pressure is the atmospheric pressure and is constant. We also can assume

- 34 -

that the mixture of gases (Argon/H2O) is homogeneous because of the big temperature

gradient and the high velocity.

The enthalpy flux is defined as

2 r hv dr=M 2 r hc dr π ρ π ρ∫ ∫ (3.4)

And we find for M:

net2 rh v dr PM= = 2 rh c dr 2 rh c dr

π ρ

π ρ π ρ∫∫ ∫ (3.5)

This would be correct if the enthalpy would include the heating of the water in the torch from

the input temperature (T0) to the boiling temperature (Tb) of water and the specific latent heat

of evaporation (lv). Including this terms we obtain:

2

netH O v w b 0

PM= +f l +C (T -T ) 2 r dr2 rh c dr

π ρπ ρ

⎡ ⎤⎣ ⎦∫∫

c (3.6)

Where f H2Ois the H2O flow rate (g/s) and the latent heat of evaporation for water is lv=22.6

105J kg-1.

The values for ρ, c and h are function of the temperature and thus also function of the radial

coordinate r. We will use tables of these variables in function of the temperature to find the

appropriate values for the Mach number. The net power is calculated from calorimetric

measurements of the cooling water of the torch. Thus the Mach number known and it is

possible to deduce the profile for the sonic speed. Using these data we obtain the velocity

profile at the exit of the torch.

- 35 -

The temperature and the velocity profile of a free jet typically have a Gaussian form. The

obtained data of the temperature can be fitted to a Gaussian curve of the following form: 2

ln 2( )( , )

(0, )t

rb zT r z T e

T z T

⎡ ⎤− ⎢ ⎥

∞ ⎣ ⎦

∞

−=

− (3.7)

With Tinf the temperature of the ambient gas.

Te mpe r a t ur e pr of i l e

1.00E+04

1.20E+04

1.40E+04

1.60E+04

1.80E+04

2.00E+04

2.20E+04

2.40E+04

-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3r ( mm)

experimental data I=400A, Ar=22.5slmexperimental data I=300A, Ar=12.5slmGaussian profile I=400A, Ar=22.5slmGaussian profile I=300A, Ar=12.5 slm

Figure 3.8: Temperature profiles fitted with a Gaussian profile

Temperature profiles were measured for different values of the torch parameters, the argon

flow rate and the power input. In figure 3.8 we can see that the Gaussian profiles fit the

experimental temperature profiles well. Tinf was chosen around 1500°C, the melting

temperature of the material of the nozzle. Observations at the exit of the nozzle show that the

temperature should be around this melting temperature. A higher current will cause a

temperature and velocity increase. Increasing the argon flow rate will result in a big velocity

increase while the temperature will only decrease a bit. For the different parameters of the

obtained results are shown in table 3.1.

- 36 -

Table 3.1: calculated velocity, enthalpy flux and momentum flux

I (A) FAr (slm) max velocity (m/s)

total enthalpy flux (J/s)

total momentum flux (kg m s-2)

300 12.5 2450 18994.48 0.121522

300 22.5 3214 21100.96 0.177161

400 12.5 2844 32878.46 0.259026

400 22.5 3721 35979.09 0.344521

[4], [21]

3.4 Volume heat source

The power input in the model is done by a velocity profile and temperature profile. This is

only the power inserted till the end of the nozzle. Between the exit of the nozzle and the

anode there is some Joule heating there. The voltage between the anode and the nozzle is

also measured and thus it is possible to calculate the extra power added in this part. The

power loss is measured by caloric measurements of the anode cooling system. From these

measurements we can calculate the power added in this volume and these results are shown

in table 3.2.

Table 3.2: Power due to Joule heating and the power loss of the anode F Ar = 22.5 slm F Ar = 12.5 slm

Current (A)

P-joule (W)

P-lost (W)

P-net (W)

Current (A)

P-joule (W)

P-lost (W)

P-net (W)

150 7919 2634 5285 / / / /

233 15119 4709 10411 231 14833 4211 10622

301 21715 6587 15128 301 21461 6240 15221

403 30158 8877 21282 403 29961 8775 21186

501 39561 11234 28327 501 39654 11204 28450

The conductivity of the plasma is a function of the temperature. It is possible to make a

conductivity profile, knowing the temperature profile at the exit of the nozzle. Assuming that

the electric field is homogeneous and the conductivity profile doesn’t change over the

- 37 -

distance d between the exit of the nozzle and the attachment point on the anode, we can

approximately calculate the dissipated power using this conductivity profile.

2( ) ( ( )) ( ( )) /P r IV T r EVA T r V A dσ σ= = = (3.8)

With d the average distance between the anode attachment and the exit of the nozzle and A

the surface of the current. In reality the anode attachment point fluctuates in time in a

reattachment process. For low values of the applied current and the argon flow rate the

attachment point is a function of these parameters. For currents higher than 300 A and 12.5

slm the attachment point will be more or less constant and approximately 13 mm (+/- 2 mm).

If we calculate the dissipated power with formula 3.8, a totally different value was obtained

than the measured power. This difference occurs because in reality the electric field is not

homogeneous and the temperature and thus the conductivity will decrease when the distance

from the exit of the nozzle increases. The measured values are more likely to be correct and

thus the obtained profile is normalized at the value of the measured power.

In FLUENT it can be simulated by using a volume heat source. The volume used is a

cylinder with a diameter of 6 mm and a height of 13 mm. The location of this heat source is

shown in figure 2.3 and is located between the plasma inlet and the anode attachment

position. First it was tried to model this added heat by a user defined function that would

calculate in function of the temperature in each cell the added power in that cell with the

formula described above. This method turned out not to work well. Now this volume is

separated in 3 concentric cylinders with respectively a radius of 1, 2 and 3 mm. With the

average power added in each of them. This gave better results and turned out to work well.

[27], [28], [29]

- 38 -

3.5 Anode jet

Electrode effects are strong sources of fluctuations of the jet properties and the instability of

the jet position. In the hybrid torch, especially the anode, which is positioned close to the

torch exit, it is one of the main sources of jet instabilities. Periodic movement of anode

attachment along the electrode surface causes changes of arc length and thus oscillations of

the power of the arc. The anode jet is formed at the anode region due to forces connected

with self-magnetic field of the arc current. Plasma flowing in the jet from the anode interacts

with the main jet and causes fluctuations of jet properties and instability of the jet position.

For the modeling the most interesting effect is the deviation of the plasma jet due to the

anode interaction. There are several forces and momentums involved as shown in the next

picture. The momentum flux MJ is flux leaving the plasma chamber. At the anode there

exists a jet with momentum flux Ma. This jet originates because of a constriction of the

conducting channel near the anode. This result in higher magnetic pressure at the anode side

and thus a jet will occur. Because of the current’s curvature there is a self magnetic force

FM acting on the jet. Considering the momentum flux balance we obtain:

J A MM M M F= + + (3.9)

Figure 3.9: Picture of the plasma jet and the anode jet. The acting momentum fluxes and

forces are indicated.

The exact values for the different contributions are not known. Measurements in this area of

the torch are extremely difficult. An estimation can be done making some approximations.

- 39 -

The anode jet is the result of the magnetic overpressure and considering the current density

homogeneous we obtain: 2

00 2/(2 )

4IP Br

μμπ

= = (3.10)

or 2

024a

IMr

μπ

= (3.11)

With r the radius of the attachment point of the current on the anode. The problem is that r

and the exact current distribution is not known.

For the self magnetic force we can use the following expression from the literature for an arc: 2

0

4sC IF μ

π=

(3.12)

With C a constant that only depends on the geometry of the current. We can combine the

anode effects in a term that only depends on the square of the current.

2

i a sM M F DI= + = (3.13)

With D a constant that only depends on geometrical factors. Experimentally this relation

was not found to be very accurate.

In FLUENT we will model the anode interaction by a volume momentum source

perpendicular with the plasma jet. The average deviation angle for different values of the

current and the argon flow rate were measured by Chumak. The value of MJ can be

calculated by integrating the mass flux profile that is obtained with the temperature and

velocity profile. Knowing the deviation angle (α) we can easily calculate Ma if we assume

that Ma is perpendicular with MJ as:

tani JM M α= (3.14)

- 40 -

Figure 3.10: The jet deflection angle and its deviation in function of the arc current

Out of the measurements of Chumak follows that the deflection angles for the parameters

used in the model (I=300, 400 A; Ar=12.5, 22.5slm) varies between 4mm and 8.6 mm. The

deflection angle is function of both the Argon flow rate as the current. When the amount of

argon increases, the momentum of the jet increases and the momentum of the anode jet are

independent of the current what result in a smaller deflection. On the other hand when the

current increases the anode jet momentum will increase and the self magnetic force, but the

momentum of the jet increases even more. In this case a bigger amount of H2O will be

converted into plasma and at the same time the velocity will increase. This results also in a

decrease of the deflection angle.

Figure 3.11: The mean attachment position and its deviation in function of the arc current

- 41 -

Out of the graphs follow that the mean attachment position for current up to 300A is almost

constant and approximately 13 mm downstream the exit nozzle. This position is used for the

momentum source in FLUENT. The source is represented by an elliptical cylinder with a

major axis of 1.5 mm and minor axis of 1 mm and a height of 0.8 mm. The calculated

momentum fluxes are shown in the next table.

Table 3.3: The calculated momentum fluxes for the anode jet.

I (A) FAr (slm) deviation angle (°) MJ (kg.m.s-2) Ma (kg.m.s-2)

300 12.5 6.9 1.21E-01 1.86E-02

300 22.5 4 1.77E-01 1.38E-02

400 12.5 8.7 2.59E-01 3.13E-02

400 22.5 5.5 3.44E-01 2.41E-02

The calculated data shows clearly that the momentum fluxes by the same current are

different.

[22], [27], [28], [29], [33]

3.6 Determination of the wood feeding rate

Using energy balance of the reactor, we can determine the feeding rate of wood for a certain

reactor temperature (Tr) and power input. A part of the supplied energy will be lost in the

torch and another part in the reactor. The rest of the power will be used to volatilize (Pdev)

the wood and to heat the syngas (Pheat,syn) till the reactor temperature. Figure 3.12 shows the

different power inputs and losses. The viscous heating is neglected and assumed to be small

compared to the other heat sources, but in the simulation it is included.

Thus we obtain:

, , , 0in lost torch lost reactor dev heat synP P P P P− − − − = (3.15)

- 42 -

dev wood fgP m h= &

0

, , ( )rT

heat syn p syn woodT

P C T m= ∫ & dT

Using these equations we can calculate the feeding rate. For the torch operating at a current

of I=400A, an argon flow rate of FAr=22.5 slm and a reactor temperature of 1400K, we

obtain a feeding rate of 0.0048 kg s-1 wood.

Figure 3.12: Different heat sources and losses

- 43 -

Chapter 4: Results of the simulation

4.1 Temperature distribution

4.1.1 Temperature distribution of the reactor walls

In the reactor the temperature at the wall is measured by nine thermometers (TIZA 101-TIZA

109) during an experiment. There are three different types used, existing out of different

materials and able to measure in a different temperature range. Figure 4.1 shows the

temperature of the walls obtained during an experiment. The temperatures differ only

slightly at different locations at the reactor walls and is approximately between 1100 and

1200°C.

Figure 4.1: Temperatures at the reactor walls during an experiment

The walls of the reactor are water cooled and thus the power loss of the walls can be

calculated from measurements of the flow rate and the temperature difference of the water

flowing in and out. The cooling circuit is not split in different parts for the different parts of

the reactor and thus the spatial distribution of the heat flux out the reactor is unknown.

Different parts of the reactor have different thermal insulation and in consequence will have

different heat losses. Especially the top part of the reactor which has a thinner insulation and

the inlet part which has no ceramic layer will probably account for a huge part of the heat

- 44 -

losses. In FLUENT it is possible to model different losses for the different parts of the

reactor and study in this way the distribution of the power losses. The total energy loss of the

reactor is around 20000 W. The calculated temperature distribution of the inner surface is

shown in figure 4.2. The obtained wall temperature distribution has a bigger temperature

differences than the ones experimentally measured and the temperature is also lower. This is

probably caused due to the fact that in this simulation all the walls were cooled uniformly. It

is visible that the top part of the reactor is hotter. In reality this part is also insulated less and

thus will account for a bigger part of the energy losses. The hotter zone on the left side is

caused by the deviation of the plasma jet. This can be concluded from figure 4.4. The gas

outlet has also a higher temperature. This part is heated more by the flux of hot gas out the

reactor.

Figure 4.2: Contours of static temperature (K) at the inner surface of the reactor.

4.1.2 Temperature distribution in the reactor

In figure 4.3 the temperature distribution of the syngas in the reactor is shown. The left

histogram shows the total temperature range, where the histogram on the right side shows

only the distribution of the temperature between 0K and 5000 K. The average calculated

temperature in the reactor was 1641 K. (I=400K, wood=0.0048) In the distribution two

maximums can be distinguished, the first around 1500 K and the second around 13000K.

- 45 -

The first maximum is the temperature of the gas in the reactor and the second belongs to the

temperature of the jet in the inlet part, the anode chamber and the reactor.

Figure 4.3: Histogram of the static temperature distribution in the reactor

The distribution of the static temperature in the xy-plane for temperature limited to 5000 K is

shown in figure 4.3. The temperature is higher in the extension of the jet. On the left side of

this region, underneath the waste inlet, there is a region of lower temperature. This is caused

by the wood entering the reactor at room temperature. The wood uses energy to heat up and

to volatilize. The distribution in the xz-plane is quite homogeneous. It is surprising that a

low density jet can heat the reactor in such a uniform way.

Figure 4.4: Contours of static temperature (K) in the xy-plane limited to 5000 K

- 46 -

4.1.3 Temperature distribution of the plasma inlet

A problem in the current reactor is the inlet tube for the plasma which is located between the

anode chamber and the reactor as indicated in figure 2.5. First it was a cylinder with a

diameter of 50 mm. During the experiments there was noticed a backflow from the reactor to

the anode chamber. The anode chamber is heavily cooled and the cooling of the syngas in

the anode chamber caused a deposit of carbon which damaged the anode. To prevent this, a

piece was introduced in the inlet tube to decrease the diameter. However during an

experiment this piece was overheated and destroyed. A photograph of this destroyed piece is

shown upside down in figure 4.5. The piece was destroyed on one side on the bottom due to

the deflection of the jet.

Figure 4.5: the destroyed piece of the inlet tube

In the future the inlet part of the reactor will be changed and have a separated cooling system.

Knowing the heat losses at this part would be helpful to improve the design of the reactor.

The inlet part of the reactor is heavily cooled to prevent damage. In one experiment this part

was destroyed as can be seen in figure 4.5. It is possible to fix a constant wall temperature at

the inlet part. In this way the heat flux out the reactor needed to obtain this temperature can

be calculated. One problem using this method is that it is not possible to control the total

energy losses of the reactor. Another is that there will be no distribution of the temperature

shown in this part. It is expected that through the deviation of the jet, one side will be a lot

warmer than the other side.

- 47 -

Three different geometries were simulated and are shown in figures 4.6, 4.7 and 4.8. In all

three cases all the input parameters were exactly the same. In table 4.1 the dimensions of the

different geometries are shown. Geometry 1 is a cylinder, geometry 2 a cone with at the top

a cylinder and geometry 3 consists out of 2 cylinders connected by the half of a sphere.

Radius 1 and radius 2 are respectively the radius of the cylinders at the bottom and at the top.

Height 2 is the height of the small cylinder at the top with radius 2.

Table 4.1: Dimensions of the different geometries. Total height (m) Radius 1 (m) Radius 2 (m) Height 2 (m)

geometry 1 0.0896 0.02575 /

geometry 2 0.04005 0.025 0.0125 0.01

geometry 3 0.04005 0.025 0.0125 0.00322

The temperature distributions for the different geometries of the inlet part are shown in

figures 4.6, 4.7 and 4.8. In these simulations the heat flux at the inlet part was chosen twice

as big as the heat flux of the other reactor walls. It is clearly visible that the deviation of the

jet causes one side to be heated more than the other. In the first two geometries the

temperature exceeds 10.000 K, which is of course not realistic and thus the heat flux should

be taken a lot higher. It was tried to increase the heat flux to model stronger cooling. This

did not work because of the huge temperature difference in these parts. When simulating, the

temperature at the cooler parts of the inlet obtained values of 0 K and lower. Of course this is

physically impossible and thus gave wrong results. But from the calculations it was possible

to conclude that the heat flux of the inlet part should be at least 100 times higher than the

average reactor heat flux to obtain possible temperatures.

For the first geometry the highest temperature is clearly located at the bottom left side. This

is also the place where in the experiment the part was destroyed due to overheating. The

distribution for the second geometry is totally different. The hottest part is in this case

located at the top, where the inlet part is the narrowest. Maybe this could cause problems in

the future when this geometry would be used. The temperature gradient is also really high.

The cooler temperature at the bottom right side is caused by an additional cooling of the wall

by the backflow out the reactor which has a temperature of aproximatly 1700K.

- 48 -

The third geometry gives clearly the best results. Not only is the wall temperature a lot

lower, but the temperature gradients are also smaller. The hottest region is also at the left

side and the result of the deflection of the jet. This region is divided in two parts, with in the

middle a cooler region. This division has two causes, first of it is caused by the cooling of

the walls by the backflow of syngas. At this region the syngas in the reactor has the lowest

temperature because it is cooled down by the heating of cold wood particles. The jet is also

wider in the yz-plane as can be seen in figure 4.25 and thus causes to heat these sides of the

inlet more and will reduce the backflow that could cool down the wall.

Another big difference between the different geometries is the height of the inlet part of the

first geometry. This is more than twice as large as the other geometries. This will result in a

smaller backflow as will be explained in paragraph 4.5 and will cause the walls to be hotter

on the right side than in the other geometries. Thus more energy has to be removed to cool

down the inlet. How longer the inlet part, how higher the influence of the deflection of the

jet. At a certain point the jet will touch the wall and the temperature at this part will of

course be high. In case of the third geometrie the jet will nowhere touch the wall.

Figure 4.6: contours of static temperature (K) for the inlet part of the first geometry

- 49 -

Figure 4.7: contours of static temperature (K) for the inlet part of the second geometry

Figure 4.8: contours of static temperature (K) for the inlet part of the third geometry

- 50 -

4.2 Plasma jet characteristics

Before the reactor was constructed, there was not known if the jet would destroy the bottom

of the reactor. The plasma torch had never operated in such conditions as presented in the

reactor. The ambient gas in the reactor has different characteristics and thus the behaviour of

the jet will be different.

Besides the velocity gradient in the jet there exists also a big temperature and density

gradient. This makes the study of such jets more difficult than non thermal jets. In the

literature low density jets have received little attention compared to their constant density

counterparts. However the available information suggests that the mixing, entrainment and

velocity decay increases when the jet density is lower than the ambient gas. In figure 4.9a

the decay of the axial velocity is shown. The velocity of the jet will decrease fast when

exiting the torch. The experimental values were measured operating the torch in the open

atmosphere and the calculated values are from the torch operating in the reactor. Out this

figure follows that the velocity decay of the torch operating in the reactor is lower than in the

open atmosphere. This can be explained by the lower density of the gas surrounding the jet

in the reactor than in the open atmosphere. The density of the syngas at the conditions in the

reactor in this simulation was around 0.1 kg m-3 as can be seen in figure 4.10. The density of

air at standard temperature and pressure is 1.168 kg m-3. In both cases the density of the jet

will be approximately the same and varies with the temperature between 0.1 kg m-3 and

0.0097 kg m-3. Thus the difference in density of the jet and the ambient gas will be smaller

in the reactor and this leads to a higher velocity.

The axial temperature decay that was simulated differs from the measured one (figure 4.9b).

The reason for this difference is not known. Only far downstream the jet, starting from 120

mm, the values are corresponding very well. From these figures we can conclude that the

behavior close to the nozzle of the simulated jet is differs with the measured jet. Some

differences were expected because of the total different environments in both cases. Not

only the temperature of the surrounding gas is different, but also for example the pressure in

the anode chamber is lower as can be seen in figure 4.18. Far downstream the resemblance

between the simulation and the measurements is very good. The characteristics of the jet at

- 51 -

this location will look a lot like the ambient gas and thus there will not be a difference

anymore between the measured and the simulated jet.

axial velocity

0

500

1000

1500

2000

2500

3000

3500

0 50 100 150 200 250 300z (mm)

velo

city

(m/s

)experimental values

calculated w ith f luent

Figure 4.9a: Axial velocity decay in millimeters from the exit of the torch

axial temperature

10003000500070009000

11000130001500017000

0 50 100 150 200 250 300z (mm)

Tem

pera

ture

(K)

calculated w ith f luent

experimental values

Figure 4.9b: Axial temperature decay in millimeters from the exit of the torch

- 52 -

Figure 4.10: Contours of density (kg m-3)

[4]

4.3 Anode influence

Figure 4.11 shows a close up of the plasma inlet part of the reactor modeled in FLUENT. It

shows the velocity vectors colored by the static temperature. The deviation due to the anode

jet and the extra heating between the inlet and the anode is clearly visible. If we compare

this obtained figure 4.11 with figure 4.12, a photograph taken of the jet in nearly the same

operating conditions as the modeled ones and colored by the light intensity, one can see that

they correspond well. The intensity in figure 4.12 can be related to the temperature. In both

cases the highest temperature is located at the end of the anode and in the middle of the jet.

The deviation in the photograph is a bit larger than in the modeled, but this can be explained

by the lower argon flow rate and thus bigger deviation angle in figure 4.12.

- 53 -

Figure 4.11: Velocity vectors colored by static temperature for a current of 400A and an

argon flow rate of 12.5 slm

Figure 4.12: Lines of the same intensity for a current of 400A and an argon flow rate of 8.5

slm

[28]

4.4 Coanda effect

If we look at the results of the simulation in figure 4.14, one can see that the deviation of the

jet becomes bigger. This can be explained by the Coanda effect.

The Coanda effect is also known as boundary layer attachment. It is the tendency of a stream

of fluid to stay attached to a surface, rather than follow a straight line in its original direction.

The principle was named after Romanian inventor Henri Coanda, who was the first to

understand the practical importance of the phenomenon for aircraft development. In this

- 54 -

case the coanda effect will result in a larger deviation of the jet in the reactor thus an increase

of the temperature at the reactor inlet.

There has been done much research to the coanda effect to offset jets with different

inclination angles. But this effect has not been studied by jets with a very high velocity and

temperature. In this case the Reynolds number will be a lot higher and thus the behaviour

different than explained in the literature. The Coanda effect is caused by entrainment of air

between the jet and the wall in the converging region. This causes a negative pressure zone

that forces the jet to deflect towards the wall and eventually to reattach to it at some

downstream location. Part of the inner shear layer fluid is deflected back upstream from the

reattachment point into the recirculation zone by an adverse pressure gradient. In figures

4.20 and 4.21 it is possible to see this recirculation flow which will also provoke the

backflow. In figures 4.14, 4.15 and 4.16 this recirculation zone is visible as the lighter blue

zone on both sides of the jet. From the Nasr article [14] we can conclude that the wall

attachment position normally will be further downstream from the nozzle if the wall would

be more inclined or when the distance between the wall and the jet is larger.

In the first and the third geometry the coanda effect does not take place. The deviation

angle a is around 6 degrees and stays almost constant. For geometry 1 it is visible that the jet

makes contact with the wall at the bottom of the inlet part. When the initial deviation angle

is larger, the coanda effect can play a role. There will even be an opposite deflection further

downstream, but this is not anymore visible on the figure. The jet will bounce at the bottom

of the inlet part and this will create a deviation to the right and away from the waste inlet,

which is worse than a deviation in the direction of the waste inlet.

In the geometry of figure 4.14, as indicated above, the boundary reattachment effect is

clearly visible. The simulations for the different geometries were done with exactly the same

parameters. The deflection of the jet can be divided in two parts. First the deflection will be

only provoked by the anode interaction. In the figure this is indicated by the angle a which is

in this case approximately 6°. From the moment the jet enters the inlet part the negative

pressure zone at the left top side increases and the deflection caused by the coanda effect

becomes clear. This location is indicated by b. The deflection angle varies from 6° till

almost 30° at the downstream location. This deviation is initiated by the anode interaction.

- 55 -

If there was not an initial deviation the jet coanda effect would not take place because of the

symmetry.

Figure 4.13: Contours of velocity magnitude (ms-1) geometry 1

Figure 4.14: Contours of velocity magnitude (ms-1) geometry 2

- 56 -

Figure 4.15: Contours of velocity magnitude (ms-1) geometry 3

The pressure distribution in the inlet parts for the different geometries is shown in figures

4.16, 4.17 and 4.18. For the geometries of figure 4.16 and figure 4.18 the pressure

distribution is almost symmetrical with respect to the y-axis and thus no deflection occurs.

The larger diameter of geometry 1 and the small height of the cylinder at the top of geometry

3 have as result that the influence of the wall is less. In the geometry of figure 4.17 the

pressure at the left side is clearly lower than at the right side. Especially at the top of the

inlet part there exists a large difference. The entrainment of gas at this location will create

the low pressure zone. The vicinity of the wall at this location and the low pressure in the

anode chamber prevents that there is a supply of gas from somewhere else to increase the

pressure. This low pressure zone will suck the jet to the wall.

- 57 -

Figure 4.16: Contours of static pressure (Pa) for geometry 1

Figure 4.17: Contours of static pressure (Pa) for geometry 2

- 58 -

Figure 4.18: Contours of static pressure (Pa) for geometry 3

Figure 4.19: Contours of pressure (Pa) between -20 and 50 Pa for geometry 3

[12], [14]

- 59 -

4.5 Backflow of syngas

The backflow of syngas to the anode chamber can cause problems as explained in paragraph

4.1.3. Using the model it is possible to test different geometries and predict if there is going

to be a backflow. However it is not possible to evaluate the magnitude of this flow thus only

a quantitative description is possible. Soon the inlet part at the reactor is going to be replaced

by geometry 2. The diameter at the top part of this geometry was decreased to prevent

backflow and at the bottom wider to prevent overheating at this location. Out the next

paragraph can be concluded that the decrease of the diameter will not result in a decrease of

the backflow. The three geometries defined in table 4.1 will be evaluated.

In Figures 4.20-4.25 a close up is taken of the top part of inlet part from two different angles

and for the different geometries. The backflow to the anode chamber is clearly visible in all

the pictures. This backflow is situated mainly at the right side (the anode side) of the inlet

part and in the xy-plane. The anode jet causes a flattening and widening of the main jet in

the yz-plane. The jet spreads out and no backflow is possible in the case of second geometry

in this plane. In the first geometry the diameter is large enough to still allow backflow in this

plane, but it is still less than in the x-y plane. The third geometry gives similar results as the

first geometry.

The reason of this backflow is the strong under pressure in the anode chamber caused by

entrainment of the ambient gas in the main jet. The pressure in the anode chamber is the

lowest in the whole reactor as we can see in figure 4.19. Figure 4.26 shows the velocity

vectors in the xy-plane in the reactor. It is clearly visible that a large amount of the syngas

flows towards the anode chamber.

Comparing the three geometries we see that the pressure in the anode chamber is the lowest

in case of the second geometry. The first and third geometries have similar pressures in the

anode chamber. The low pressure is the result of entrainment of ambient gas in the jet.

Decreasing the radius at the top of the inlet will give a decrease in the pressure and thus will

not lead to a decrease of the backflow. Thus the decrease of the inlet radius is not a good

solution for this problem.

In figures 4.27-4.29 the contours of moll fraction of syngas are shown. Out these figures we

can conclude that the backflow consists mainly of syngas out the reactor. The moll fraction

- 60 -

of syngas in the reactor was for all simulations the same and 0.89. The mol fraction in the

anode chamber is different for the three geometries. For the first geometry it is around 0.7

and for the second and third around 0.85. For the latter ones this is almost the same as the

moll fraction in the reactor. For both geometries the backflow of syngas occurs mainly at the

right side (the anode side). At the left side there is less backflow and also the mole fraction

of syngas is lower. The different lenghts of the inlet parts are the main reason for this mol

fraction difference. Thus a solution to decrease the amount of syngas in the anode chamber

could be an increase of the length of the inlet. However this would also increase the wall

temperature and thus the energy losses and also decrease the velocity and turbulency in the

reactor. From these figures it is possible to conclude that there is a lot of entrainment of the

surrounding gas and that it occurs very fast. After less than 20 mm the surrounding gas

already reaches the center of the jet and when reaching the inlet part, half of the jet exists out

of syngas.

Figure 4.20: Velocity vectors colored by velocity magnitude in ms-1 in the xy-plane for

geometry1

- 61 -

Figure 4.21: Velocity vectors colored by velocity magnitude in ms-1 in the yz-plane for

geometry1

Figure 4.22: Velocity vectors colored by velocity magnitude in ms-1 in the xy-plane for

geometry 2

- 62 -

Figure 4.23: Velocity vectors colored by velocity magnitude in ms-1in the yz-plane for

geometry 2

Figure 4.24: Velocity vectors colored by velocity magnitude in ms-1in the xy-plane for

geometry 3.

- 63 -

Figure 4.25: Velocity vectors colored by velocity magnitude in ms-1in the yz-plane for

geometry 3.

Figure 4.26: Velocity vectors colored by velocity magnitude in ms-1 limited to 200ms-1 in the

yx-plane geometry 3.

- 64 -

Figure 4.27: Contours of moll fraction of syngas for geometry 1

Figure 4.28: Contours of moll fraction of syngas for geometry 2

- 65 -

Figure 4.29: Contours of moll fraction of syngas for geometry 3

4.6 Particle tracking

During the stay in the reactor the inserted wood particles will exchange momentum, energy

and mass with the continuous phase. This happens as described in chapter 1 in paragraphs

2.6, 2.7 and 2.8 according to the formulas 2.6, 2.8 and 2.12. The rate of this change will

mainly depends on the particle diameter, mass, temperature, velocity and the temperature of

the surrounding gas.

The particles will gain momentum due to gravity and the drag force. This force is inversely

proportional with the second power of the particle diameter and proportional with the

difference of the velocity between the fluid and the particle. The temperature dependence

lies in the molecular viscosity of the continuous phase. The energy transfer depends on the

size of the surface of the particle, the mass and the temperature difference between the

particle and the ambient gas. A part of the heat will also be used to volatilize the particle. The

rate of mass exchange is determined by the temperature dependence of the Arrhenius

equation and by the volatile fraction that still remains in the particle.

- 66 -

Dissimilarities in the behaviour of particles with different diameters are expected. The heat

and momentum transfer for bigger particle will be influenced by the evaporation. To study

the effect of the initial size, some simulations with different particle sizes were made. In

experiments the particle diameters vary between 1 e-4 m and 5 e-3 m. For the simulations

three groups of particles were studied with their diameters following a Rosin-Rammler

distribution. The Rosin-Rammler distribution function is based on the assumption that an

exponential relationship exists between the particle diameter (d) and the mass fraction (Yd )

of particles with diameter greater than d:

( )'

ndd

dY e−

= (4.1)

Where d’ is the mean diameter and n the spread parameter. The dimensions of the particles

for the different groups are given in table 4.2.

Table 4.2: the different particle groups and their properties Min size

(mm)

Max size

(mm)

Mean size

(mm)

Spread

parameter

Group 1 0.1 0.5 0.3 8

Group 2 0.5 1.5 1.0 8

Group 3 3 5 4 8

First the path lines of virtual mass less particles released at the waste inlet were calculated

and are shown in figure 4.30 colored by the velocity magnitude which is limited in this figure

to 100 ms-1. This shows the flow field inside the reactor. It is clearly visible that the

majority of the flow lines immediately go from the waste inlet to the jet because of the low

pressure at the anode chamber and than straight down to the bottom of the reactor. They will

turn around a couple of times in the reactor, re-entering the jet, before leaving the reactor

through the gas outlet. One flow line enters the anode chamber and as explained can this

backflow cause problems.

- 67 -

Figure 4.30: The path lines of virtual mass less particles injected at the waste inlet and

colored by the velocity magnitude (m/s)

The particle trajectories for the smallest particles are shown in figure 4.31. We would expect

that the trajectories of these particles follow fairly well the flow lines in the reactor. From

the moment they are inserted in the reactor, the particles will feel immediately the drag force

and deviate from the path defined by the gravity. It seems that they are repelled from the jet

and flow to the reactor wall in contrary to the mass less particles. It takes a short time before

they are totally evaporated and none of these particles reach the bottom of the reactor.

Figure 4.31: Particle trajectories of particles from group 1, left colored by the particle

diameter (m), right colored by the particle static temperature (K)

- 68 -

In figure 4.32 and 4.33 some trajectories for particles of group 2 are shown. The particles

which are inserted close to the plasma inlet will be sucked in the jet immediately. The others

will first be repelled by the flow next to the jet to the reactor wall. In this case gravity has

already a bigger impact. When released at the waste inlet they will fall down and the drag

force only becomes significant when reaching the reactor. A part of the particles are able to

reach the bottom of the reactor before being evaporated and fly back up.

Figure 4.32: Particle trajectories of particles of group 2 colored by particle diameter (m).

- 69 -

Figure 4.33: Particle trajectories of particles of group 2 colored by the particle static

temperature (K).

The trajectories for the largest particles are shown in figure 4.34, 4.35 and 4.36. Until the

particles are in the reactor they almost only feel the gravity force. It is visible in figure 4.34

that the smaller particles will deviate more to the right due to the drag force than the larger

ones. Again some particles are sucked by the backflow into the inlet part while the rest is

repelled to the wall by the jet. If the waste inlet would be located further from the plasma

inlet, the amount of particles entering the plasma inlet part could be reduced. In figure 4.35

some particle are even able to reach the anode chamber and are evaporated there. The

majority of the particles are evaporated inside the reactor while flying around. However a

sufficient large fraction (12.8%) of the particles escapes from the reactor to the gas outlet

before being evaporated entirely.

- 70 -

Figure 4.34: Particle trajectories of particles from group 3 colored by the particle diameter

(m).

Figure 4.35: particle trajectories of particles of group 3 colored by the particle static

temperature (K).

- 71 -

Figure 4.36: Particle trajectories of particles of group 3 colored by the particle residence time

(s).

If we look at the contours of mass source we observe large differences between figures 4.37,

4.38 and 4.39 for the particles with different sizes. The smallest particles are almost all

evaporated at the same location. This happens when they have obtained a sufficient high

temperature. The contours of mass source for the particles of group 2 are already spread out

more, but still mainly underneath the waste inlet.

The largest particles are evaporated everywhere in the reactor. Some particles are gasified in

the jet, but the majority at the top of the reactor and close to the wall. This can be explained

by the fact that the particles will stay longer at these locations when reaching them because

of the low local velocity. If we combine figures 4.35 and 4.36 we can see that the

temperature of the particles on average is higher at the top of the reactor and that residence

time is also higher. Only a small part of the large particles is evaporated in the jet, although

the temperature is very high at this location. The very short residence time and the long time

to heat larger particles is the reason for this. At the lowest point of the reactor, at the left

bottom on the figure, we can observe that there were some particles collected which stopped

moving and evaporated totally at this location. The velocity at this point is very low and

- 72 -

gravity will assist the particles to reach this location. In the real reactor at this location the

formed slag is collected. We can conlcude that this is the right place, because the non

volatile components will eventually stop moving at this location. It can be seen that it takes

longer before gasification starts for larger particles. They first have to obtain a sufficient

temperature before the evaporation starts.

Figure 4.37: Contours of discrete phase mass source in 3D (kg/s) plotted together with

contours of static temperature (K) in the xy-plane for particles of group 1.

- 73 -

Figure 4.38: Contours of discrete phase mass source in 3D (kg/s) for particles of group 2.

Figure 4.39: Contours of discrete phase mass source (kg/s) for particles of group 3.

- 74 -

In table 4.3 the average, minimum and maximum elapsed time for the different particles

groups is given. This information indicates how much time the particles spent in the domain

before they escaped, were aborted or evaporated. The difference in evaporation time

between the particles of group 1 and 2 is rather small. The particles have to obtain a certain

temperature before the gasification can start. The time to reach this temperature is not very

different for both groups, because the energy available at this region is limited by the supply

of energy from other regions. In figure 4.4 it is visible that the inserted wood will cool down

the syngas underneath the waste inlet a couple of hundred degrees. The particles of group 3

need a lot longer to heat up what also can be seen in figure 4.35. In this case the evaporation

rate is not limited by the energy supply of a particular region, but by the time to heat the

larger mass. The average evaporation rate for a particle is also given in table 4.3. The larger

particles have a higher average evaporation rate because they do not depend on the limited

energy content of a region and have a larger surface. In table 4.3 the evaporated mass

fraction is given for the different groups of particles. The wood was defined to exist out of

99.2% volatiles. We can see that 99.19% of the mass is gasified for the evaporated particles.

Thus we can conclude that all the volatile content of the particles is evaporated. The rest are

the non volatile components and these will remain as char in the reactor. Interesting is that

the escaped particles on average are only evaporated for 10.59 % while they still stay on

average half of the time of an evaporated particle in the reactor. Thus we can conclude that

in the first part of their stay the particles will mainly use the energy transferred to obtain a

higher temperature and evaporate in the second part. In the three cases the same amount of

wood was inserted and thus the total heat transfer used for the evaporation will almost be the

same. Escaping particles will be disadvantageous in two ways. First of all they will pollute

the produced syngas when leaving the reactor. Second they will cause an extra heat loss

because their heating was almost useless.

- 75 -

Table 4.3: Particle properties for the different groups Elapsed time (s) Particle

diameter Fate Number particles tracked Min Max Avg Std Dev

Evaporated 10397 4.46E-01 8.41E+00 1.13E+00 4.71E-01

Escaped 1336 2.51E-01 2.17E+00 6.00E-01 2.62E-01 Group 3

Aborted 0 0 0 0 0

Evaporated 11904 1.81E-01 1.01E+00 3.59E-01 1.03E-01

Escaped 0 0 0 0 0 Group 2

Aborted 0 0 0 0 0

Evaporated 11903 1.42E-01 2.48E+00 3.35E-01 1.40E-01

Escaped 0 0 0 0 0 Group 1

Aborted 1 2.00E-01 2.00E-01 2.00E-01 4.29E-05

Particle diameter Fate

Escaped Fraction %

average evaporation rate per particle g/s

Evaporated mass fraction (%)

Total heat transfer fluid-particles (W)

Average total heat transfer rate (W s-1)

Evaporated 0.166 99.19 2.04E+04 1.81E+04

Escaped 0.0312 10.59 1.17E+03 1.95E+03 Group 3

Aborted 12.8 0 0 0 0

Evaporated 0.00816 99.19 2.31E+04 6.43E+04

Escaped 0 0 0 0 Group 2

Aborted 0 0 0 0 0

Evaporated 0.000236 99.19 2.32E+04 6.93E+04

Escaped 0 0 0 0 Group 1

Aborted 0 0.000395 0 1.71E+00 8.55E+00

- 76 -

Chapter 5: Evaluation of the Ar flow rate

of the hybrid low pressure torch

5.1 Mass spectrometer

To determine the composition of a gas sample, a mass spectrometer is used. A mass

spectrometer always contains the following elements: a devise to introduce the substance, an

ionizer, several analyzers to separate the various produced ions, a detector to count the ions

and finally a data processing system. The type of mass spectrometer used was a quadrupole

mass spectrometer. Ions generated by the ion source are transmitted to the quadrupole mass

filter, where they are separated with respect to their m/e ratio. The Faraday detector serves as

a collector for the ions reaching the detector. The sensitivity is the ratio between the number

of ions reaching the detector and of the ions produced in the source. The sensitivity differs

for different types of the ions and also slightly for different types of mixtures and should be

determined by a calibration.

5.2 Calibration

To obtain accurate results using the mass-spectrometer, it is important to make a good

calibration. Mass spectra only provide intensities of definite mass numbers and to derivate

partial pressures and concentration this calibration is necessary. In this application the kind

of gas can be directly identified on the basis of his discrete characteristic masses without the

possibility of mutual interferences. To obtain reliable calculations prior knowledge of the

presented involved gasses is needed and their approximate concentration. The accuracy of

the measurements depends mainly on the calibration.

- 77 -

The aim of the calibration procedure is to determine calibration factors. With the knowledge

of these calibration factors and the current intensities it is possible to obtain the

concentration. (Concentration: Intensity/ Calibration factor)

The calibration exist out of measurements of gas mixtures which are obtained by mixing

various gases while controlling their flow rates with high precision flow controllers

calibrated for the respective gases. First some time has to be waited until the gases are well

mixed and the ion currents of the base peaks are stable. Then the spectrum of the mixture

can be obtained and analyzed in the following way.

nn

n

ICS

+

= (5.1)

Where Cn is the partial pressure, I+n the ion current and Sn the sensitivity of component n.

The concentration is than found as:

% n

nn

CC

=∑

(5.2)

The composition of the gas mixture is than compared with the volumetric ratio of the gas

components obtained from the spectrum. From these we can obtain the right sensitivities for

each mixture.

In this case the calibration was done with mixtures of Ar, H2 and N2. Because the mass

spectrometer has some problems measuring H2, there was first a calibration done with a

mixture of Ar and N2.

Ar-N2 mixture

0

0.00005

0.0001

0.00015

0.0002

0.00025

0.0003

0 20 40 60 80 100%

sens

itivi

ty

ArN2

Figure 5.1: Ar and N2 sensitivity for different mixtures of N2-Ar

- 78 -

From the measurements of these mixtures, the sensitivity for N2 and Ar was obtained. Figure

5.1 shows these sensitivities in function of the percentage Ar or N2 and it is clear that they

are almost constant.

On the other hand the sensitivity of the spectrometer with respect to hydrogen is everything

but constant and is shown in the following graph. Using the fixed sensitivities for Ar and N2,

it is possible to obtain for a certain measurement the right sensitivity of H2 and thus the right

concentrations.

Ar-N2-H2 mixture

y = 0.0007x-0.2683

0.0002

0.00025

0.0003

0.00035

0.0004

0.00045

0 20 40 60 8% H2

sens

itivi

ty

0

Figure 5.2: H2 sensitivity for different mixtures of N2-Ar-H2

In figure 5.3 an example of a mass spectrum is shown. There are peaks at the mass numbers

4, 20, 28, 32 and 40, for respectively H2, double ionized Ar, N2, O2 and Ar. Using the

formulas above together with the sensitivities obtained from the calibration and the mass

spectrum it is possible to calculate the composition.

- 79 -

Mass spectrum

0.00E+00

4.00E-06

8.00E-06

1.20E-05

1.60E-05

2.00E-05

2.40E-05

2.80E-05

0 10 20 30 40 5mass number

ion

curr

ent

0

Figure 5.3: example of an obtained mass spectrum

[4], [12]

5.3 Argon flow rate

The torch used in the low pressure chamber is a hybrid gas-water plasma torch. This torch is

similar as the one used in the reactor for waste treatment. It has some adjustments to work in

a low pressure environment. The diameter of the exit nozzle is narrower and the water

stabilized chambers only have one water outlet. A scheme of the hybrid torch is shown in

figure 1.6. The plasma exiting the torch will be a mixture of argon and water plasma. To

calculate the flow rate of argon, the losses of argon have to be subtracted from the amount of

argon entering the torch. When we look at the scheme of the hybrid torch it is logic that a

part of the argon entering the torch will be subtracted at the water outlet in the stabilization

chamber together with the water. To calculate this fraction, the composition of the gas

which was pumped away together with the water out of the stabilization chamber was

measured with a mass spectrometer. The flow rate of this gas pumped away was also

measured. A scheme of the measurement is shown in figure 5.4. The amount of argon used

as plasma is than easily calculated. The total plasma flow rate will be the sum of the water

and argon flow rate.

- 80 -

The gas mixture that is pumped away together with the water out of the torch goes to the

water basin as can be seen in figure 5.4. The pump of the water basin pumps always at a

same rate. The pressure in the basin is regulated by an air inlet to the basin. However the

flow rates measured changed sometimes without a known reason. Probably it has to do

something with the pump of the low pressure water basin. Even when the valve which

controls the air input seemed closed, independent of the torch parameters the flow rates

measured were different. Sometimes it was not possible to obtain measurable conditions

because the flow rates were too high.

Figure 5.4: Scheme of the experimental set up.

It is assumable that a part of the gas measured at the flow meter exists of water vapor. Before

the composition is measured by the MS this part is frozen out to prevent damage of the

spectrometer. Thus it is not measured by the mass spectrometer, but is included in the flow

rate and would lead to an overestimation of the amount of argon pumped away. To estimate

the amount of water vapor, we can assume that in the gas basin there exists a saturated

amount of H2O vapor. An easy calculation using partial pressures learns us that this only

would result in a few percent of water vapor. This amount would be negligible comparing to

the resolution of the measurement. Nevertheless to be sure, there were done measurements

- 81 -

using a trace gas. There were always done two kinds of measurements for different values of

the torch parameters. The first adding a known flow rate of N2 , measured with a separated

flow meter, to the gas mixture before measuring the flow rate and composition and a second

without this trace gas. Comparing these measurements it is possible to calculate the amount

of H2O vapor. The differences in the concentrations between these measurements were less

than 1% and thus too small to calculate the amount of H2O vapor. It is possible to conclude

that the amount of H2O vapor is negligible.

For different values of the torch parameters, between 45% and 80 % of the argon entering the

torch leaves the exit nozzle as plasma. In graph 5.5 and graph 5.6 this percentage of argon is

plotted against the current for respectively pressures of 40 and 80 kPa in the vacuum

chamber. It can be seen that when the current increases this percentage will decrease. For

the torch working at atmospheric pressure the opposite relation was observed. The reason for

this decrease is probably a combined action of some factors and not easy to explain.

Percentage of argon used as plasma, 40 kPa

6062646668707274767880

200 220 240 260 280 300Current (A)

%

17.5 slm22.5 slm

Figure 5.5: Percentage of argon used as plasma in function of the current for the torch

working in the low pressure chamber at a pressure of 40 kPa for different values of argon

flow rates.

- 82 -

Percentage of argon used as plasma, 80 kPa

40

45

50

55

60

65

70

200 220 240 260 280 300Current (A)

%

12.5 slm17.5 slm22.5 slm

Figure 5.6: Percentage of argon used as plasma in function of the current for the torch

working in the low pressure chamber at a pressure of 80 kPa for different values of argon

flow rates

When the argon flow rate entering the torch increases, a higher percentage of the Argon

leaves the torch. This relation is shown in graph 5.7. This increase is rather low compared to

the decrease due to an increase in current. When the flow rate of argon increases the amount

that is pumped will increase also but the percentage argon pumped away will decrease. It is

logic that when there is a larger amount of argon inserted that there will be pumped away

more, but that the percentage of argon leaving the torch as plasma will be bigger. Thus

doubling the argon flow rate entering the torch will result in an increase of argon plasma

which is more than double this amount.

- 83 -

Percentage of argon used as plasma

40

45

50

5560

65

70

75

80

10 12 14 16 18 20 22 24Argon flowrate (slm)

%

200 A, 80 kPa300 A, 80 kPa200 A, 40 kPa300 A, 40 kPa

Figure 5.7: Percentage of argon used as plasma in function of the argon flow rate for the

torch working in the low pressure chamber for different values of the current.

When the pressure in the vacuum chamber decreases from 80 kPa to 40 kPa, the fraction of

argon used as plasma increases. If we assume that there is a physical connection between the

vacuum chamber and the torch this can be easily explained. In that case a lower pressure in

the vacuum chamber will suck stronger when it is at low pressure and thus the suction of the

pump to the water basin will be relatively smaller.

Percentage of argon used as plasma, 300 A

45

50

55

60

30 40 50 60 70 80 90

Pressure (kPa)

%

17.5 slm

22.5 slm

Figure 5.8: Percentage of argon used as plasma in function of the pressure for the torch

working at 300 A in the low pressure chamber for different values of argon flow rates.

- 84 -

Percentage of argon used as plasma, 200 A

50

55

60

65

70

75

80

30 40 50 60 70 80 90

Pressure (kPa)

%

12.5 slm

17.5 slm

22.5 slm

Figure 5.9: Percentage of argon used as plasma in function of the pressure for the torch

working at 200 A in the low pressure chamber for different values of argon flow rates.

- 85 -

Chapter 6: Conclusion In this work a CFD model was used to model the plasma chemical reactor which is located at

the IPP in Prague. Using such a model can be helpful to understand physical processes

acting in the reactor. Nevertheless a lot of simplifications were made and it of course it is not

possible to include all processes which are present in reality. The input parameters are never

exact. For example one critical point is the estimation of the pre exponential factor of the

Arrhenius equation used to describe the evaporation rate. Due to this, the results obtained

using such simulations should always be interpreted with care. However it is a very useful

way to get a better understanding of the processes acting in the reactor.

Using the simulations it was demonstrated that the behaviour of the jet working in the reactor

is different than the jet operating in the open atmosphere. This is caused by the difference of

the properties of the gas surrounding the jet. It was shown that it is possible to heat the

entire reactor quite homogeneous using only such a small low density plasma jet and that the

heat distribution is influenced by the wood input.

The origin of the backflow to the anode chamber was discovered and turned out to be a low

pressure in the anode chamber created by the entrainment of the surrounding gas into the jet.

The solution to reduce the backflow by reducing the diameter turned out to have no effect or

even increased the backflow. A longer plasma inlet reduces the backflow, but has also some

disadvantageous. This will increase the wall temperature and decreases the velocity and

turbulence in the reactor. Besides this, the shape of the inlet will also influence the flow

pattern and can result in a huge additional deviation of the jet. To develop an inlet part for the

plasma which fulfills all the required conditions is a difficult job. The proposed geometry

gives good results for the wall temperature, but does not reduce the backflow.

It was demonstrated that the dimensions of the wood particles influences the mass, heat and

momentum transfer between the particles and the continuous phase. When the particle size is

large (3-5 mm), some are able to escape from the reactor to the gas outlet. Thus it is

preferable to use smaller particles, to be sure that they all evaporate. The rate of evaporation

of small particles is mainly limited by the available heat supply to the region underneath the

wood input.

- 86 -

We can learn a lot from such simulations as demonstrated. This model is not limited to study

the parameters evaluated in this work. It could also be used to investigate different processes

as done so far. Some parts of the model still leave some room to be improved. Some

physical processes are not yet included and there is still some room to make the input and

boundary conditions more accurate. Thus using such models more in the future can lead to

a better understanding and design of the reactor.

- 87 -

Literature list [1] G. Van Oost, Plasma Physics, course notes, 2006-2007 [2] J. V. R. Himberlein, C. W. Kimblin, A. Lee, Nature of the Electric Arc, Westinghouse Research Development Center, Pittsburgh, Pennsylvania [3] B. Defoort, Pyrolysis of biomass with hybrid gas-water plasma torch for syngas production., powerpoint presentation (september 2006) [4] T. Kavka, Study of thermal plasma jets generated by dc arc plasma torches used in plasma spraying applications, Ph.D Thesis (2006) [5] D. Samson, Valorisatie van waterstofproductiein een plasmachemische reactor, thesis (november 2003) [6] G. Van Oost, M. Hrabovsky, V. Kopecky, M. Konrad, M. Hlina, T. Kavka, A. Chumak, E. Beeckman, J. Verstraeten, Pyrolysis of waste using a hybrid argon-water stabilized torch, Vacuum, 80, 1123-1137, 2006 [7] M. Hrabovsky, V. Kopecky, M. Konrad, M. Hlina, T. Kavka, G. Van Oost, E. Beeckman, J. Verstraeten, Gasification of Biomass in Water-Stabilized DC Arc Plasma, 2005 (3) [8] M. Hrabovsky, M. Konrad, V. Kopecky, M. Hlina, T. Kavka, G. Van Oost, E. Beeckman, B. Defoort, Pyrolysis of wood in arc plasma for syngas production, 2006 (2) [9] I. Hirka, J. Jenista, M. Hrabovsky, Modelling of Mixing of Steam Plasma Jet with Steam Atmosphere in Thermal Plasma Reactor, 2005 [10] M. Hlina, M. Hrabovsky, V. Kopecky, M. Konrad, T. Kavka, Plasma gasification of wood and production of gas with low content of tar, Czech. J. Phys. 56, 2006 [11] M. Hlina, M. Hrabovsky,V. Kopecky, M. Konrad,T. Kavka, S. Skoblka, Plasma gasification of wood and production of gas with low content of tar. Czechoslovak Journal of Physics, 56 (D) 2006 [12] Wikipedia (2007), www.wikipedia.org [13] O. Chumak, M. Hrabovský, V. Kopecký, Investigation of Anode Attachment in dc Arc Plasma Spraying Torch with External Anode, 2003 [14] A. Nasr, J. C.S. Lai, The effects of wall inclination on an inclined offset jet. , 2000

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[29] O. Chumak, M. Hrabovsky, V. Kopecky, T. Kavka, Interaction between anode attachment and plasma jet in dc arc plasma spraying torch, Phys. of Low Tem. Plasma, Kiev, Ukraine, p6.11.111-p, 2003. [30] V. Sember, T. Kavka, V. Kopecky, M. Hrabovsky, Comparison of spectroscopic and enthalpy probe measurements in H2O-Ar thermal plasma jet, 2003 [31] J. Jenista, Numerical Modeling of Hybrid Stabilized Electric Arc With Uniform Mixing of Gases, IEEE Transactions on plasma science, Vol. 32, NO. 2, April 2004 [32] M. Hrabovsky, Generation of thermal plasmas in liquid stabilized and hybrid dc-arc torches, Pure Appl. Chem., Vol.74, No. 3, pp. 429-433, 2002 [33] M. Hrabovsky, DC Arc thermal plasmas- generation, diagnostics and applications [34] Hybrid plasma TGV, powerpoint ENVITECH [35] FLUENT 6.2 users guide [36] Gambit 2.2.30 users guide

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