2

An ASABE Meeting Presentation

Paper Number: 064060

Three-Dimensional Numerical Simulation Model of Biogas Production for Anaerobic Digesters

Binxin Wu, Research Associate Dept. of Mechanical and Manufacturing Engineering, University of Manitoba, Winnipeg, MB, R3T 5V6, Canada. bxwulk@hotmail.com

Eric L. Bibeau, Assistant Professor Dept. of Mechanical and Manufacturing Engineering, University of Manitoba, Winnipeg, MB,

R3T 5V6, Canada.

Kifle G. Gebremedhin, Professor Dept. of Biological and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA

Written for presentation at the 2006 ASABE Annual International Meeting

Sponsored by ASABE Oregon Convention Center

Portland, Oregon 9 - 12 July 2006

Abstract. A review of the modeling of biogas production from anaerobic digesters is first conducted. A three-dimensional numerical simulation model that predicts biogas production from a plug-flow anaerobic digester is developed. The model is based on the principles of continuity, energy, and species transport. A first-order kinetic model is used to predict the chemical reactions and BOD (Biological Oxygen Demand) in the digestion process. A user-defined function for computing the chemical source terms of the finite rate model is developed. The anaerobic digestion and simulation are conducted using Fluent 6.1 to predict the temperature profile and concentration distribution in the digester. Model predictions are validated against experimentally measured biogas production data obtained from the literature. The results agree within 5%.

Keywords. Numerical Simulation, Anaerobic Digester, Chemical Reaction, Biogas Production.

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Introduction Anaerobic digestion of cow or swine manure is a source of renewable energy. The anaerobic

digestion process reduces the solid content of the influent and produces less offensive odors. The

process involves transformation of the organic compounds, by microorganisms, into microbial

biomass and other simpler compounds, eventually releasing water, carbon dioxide, and methane.

Biogas production using anaerobic digesters has been experimentally and theoretically studied

since the 1960s (Buswell and Mueller, 1962). Biogas production models have evolved from

simple models (Jewell, 1978; Chen and Hashimoto, 1978; Safely and Westerman, 1992, 1994;

Toprak, 1995; Hobbs et al., 1999; Andara and Esteban, 1999; Masse and Droste, 2000) to a

complex model (Scott and Minott, 2002). In the simple models, if any of the assumed

parameters such as digester volume or slurry temperature is changed, the models become no

more valid. The complex model (Scott and Minott, 2002) contains more input parameters

compared to the simple models. The inputs include: hydraulic retention time, initial volatile

solids concentration, bacterial growth rate at fixed digester temperature, digester volume, and

daily flow rate of manure influent. However, these models are one-dimensional (the spatial

parameters are not taken into consideration), and it is known that biogas production is sensitive

to digester temperature, pH of the liquid manure, and non-uniformity of flow pattern of liquid

manure inside the digester. In previous studies (Hashimoto et al., 1981; Safely and Westerman,

1992, 1994; Scott and Minott, 2002), these parameters were assumed to be constants. To our

knowledge, no three-dimensional numerical simulation model that predicts biogas production

from local flow conditions for mixing-flow and plug-flow type digesters has been reported.

Objectives:

The objectives of this study are to:

(1) conduct a comprehensive literature review on modeling biogas production from anaerobic

digestion,

(1) develop a general and fundamentally-based three-dimensional numerical model that predicts

biogas production from plug-flow type digesters, and

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(2) validate the model predictions against experimental data obtained from the literature.

Literature Review Buswell and Mueller (1962) developed a model that predicts methane production from chemical

composition of degradable waste. The model is expressed as

422 )482

()482

()24

( CHban

COban

OHba

nOHC ban −+++−⇔−−+ (1)

where, ban OHC is organic matter, OH2 is water, 2CO is carbon dioxide, 4CH is methane, a, b,

and n are dimensionless coefficients.

Jewell (1978) developed an empirical model for biogas production for a plug-flow digester and is

expressed as

HRTSSBG bbmethane /)(5.0 10 −= (2)

where, 0bS is influent biodegradable volatile solides (BVS) concentration (g/L), 1bS is effluent

BVS concentration (g/L), HRT is hydraulic retention time (days), and methaneBG is the volumetric

methane production rate: volume of gas produced per digester volume per day (L/ (L*day).

Chen and Hashimoto (1978) developed a model that predicts methane production rate and is

expressed as

0 0*

(1 )* 1v

m

B S K

HRT HRT Kγ

µ= −

− + (3)

where, vγ is methane production rate (L of 4CH per L digester volume per day), 0B is ultimate

methane yield (L 4CH /g VS added), 0S is influent volatile solid concentration (g/L), K is kinetic

parameter (dimensionless), and mµ is maximum specific growth rate ( 1−day ). The K parameter

was empirically determined from

5

)051.0( 00206.06.0 SeK ⋅+= (4)

The mµ value was calculated from (Hashimoto et al., 1981)

0.013* 0.129m Tµ = − (5)

where, T is digester temperature ( C0 ).

Bryant (1979) studied microbial methane production. He investigated the relationships of three

general metabolic groups of bacteria or stages of fermentation involved in methane fermentation.

The three metabolic groups of bacteria include: first-stage-fermentative bacteria, second-stage-

2H -producing acetogenic bacteria, and stoichiometry and kinetics of fermentation.

Hill (1982a, 1982b, and 1982c) performed computer analysis of microbial kinetics of methane

fermentation to show: (a) maximum volumetric methane production, and (b) maximum total

daily methane production to design the continuous flow anaerobic digester. He analyzed methane

fermentation kinetics to produce a set of optimized design criteria for steady-state digestion, and

developed a dynamic computer model to predict digester operating conditions (i.e., retention

time, loading rate, and temperature) for four major animal types (dairy, poultry, swine, and beef).

Hashimoto (1983) studied the effects of temperature (35 C0 and 55 C0 ), influent volatile solid

concentration and hydraulic retention time on methane production from swine manure.

Hashimoto (1984) experimentally determined the K parameter specific for swine manure. Later,

Hashimoto et al. (1994) discussed about commercializing the technology of methane production

from animal waste, and described the design and construction of a centralized anaerobic

digestion facility that converts dairy manure into electrical energy and fertilizer.

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Fischer et al. (1984) operated an anaerobic digester using swine manure at high influent volatile

solids concentration, and evaluated the relationship between methane production per gram of

volatile solids added, and methane production per volume of digester, to hydraulic retention time

and influent volatile solids concentration.

Pavlostathis and Gossett (1986) examined the preliminary conversion step in detail by

considering mechanisms such as cell death/lysis, hydrolysis of particulate dead biomass,

acidogenesis, and methanogenesis. A kinetic model was proposed to describe digester

performance and predict effluent quality.

Costello et al. (1991a) developed a mathematical model of a high-rate anaerobic treatment

system by defining the biological make-up of an anaerobic ecosystem, the physico-chemical

system, and the reactor process. The overall reactor equations were described and included the

biological rate equations, and inhibitions and interactions within the anaerobic system. The

physico-chemical reaction system determined the ionic concentration of soluble components in

the reactor. Later, Costello et al. (1991b) validated their model against results obtained from two

laboratory-scale reactors and a pilot-scale.

Safely and Westerman (1992) determined the relationship between methane yield and digester

temperature in a low-temperature lagoon digester. The equation was expressed as

0.216 0.00934*B T= + (6)

where, B is methane production ( VSkgCHm /43 ), and T is digester temperature ( C0 ).

Safely and Westerman (1994) evaluated the performance of laboratory-scale anaerobic digesters

fed with dairy and swine manure at loading rates of 0.1 and 0.2 3/kgVS m day− over a

temperature range of 10 C0 -25 C0 , and reported the following equations to estimate methane

yield:

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TB 0053.01153.0 += (for dairy at a loading rate of 0.1 kgVS/m3-day ) (7a)

TB 0063.00820.0 += (for swine at a loading rate of 0.2 kgVS/m3-day) (7b)

TB 0053.02011.0 += (for swine at a loading rate of 0.1 kgVS/m3-day ) (7c)

TB 0044.03177.0 −= (for swine at a loading rate of 0.2 kgVS/m3-day) (7d)

Toprak (1995) found the following power law relationship between biogas production and ambient air temperature:

127.1)(241.1 aTR = (8)

where, R is biogas production ( 2/L m day ), and aT is ambient air temperature ( C0 ).

Hobbs et al. (1999) developed a model for methane and carbon dioxide mass emissions from pig

slurry. Methane emission was expressed as

4CH = 04.10266.0)105( 21 −+×× − tt (9)

where, CH4 = mass of methane emission (mg), and t is time (hours).

Kayhanian and Tchobanoglous (1996) developed a kinetic model to simulate the biodegradation

of the organic fraction of municipal solid waste in a high-solids complete-mix, continuous-flow

anaerobic digestion process. A mass balance correction factor was used to account for water

incorporated into the production of biogas and water vapor present in the biogas. The model

predicts the first-order kinetic constant.

Andara and Esteban (1999) developed a kinetic model in an anaerobic digestion process.

Specific production of methane in anaerobic digestion of solid fraction of screened piggery waste

was adjusted by dividing the process into two stages. The predictions from this two-stage model

were validated against experimental data and the results agreed very well. The equation for the

first stage model is expressed as

*0 0 0/ ( / ) tB B X Y S eµ= (10)

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where, B is methane production ( kgm /3 ), 0B is specific methane production at infinite hydraulic

retention time ( kgm /3 ) (note that B approaches 0B when HRT approaches infinity), 0X is initial

microorganisms concentration (g/L), Y is cellular output constant, 0S is initial substratum

concentration (g/L), µ is special cellular growing rate (day-1), and t is time (days). The equation

for the second-stage model is expressed as

( * )0 0( ) / K tB B B e −− = (11)

where, K is kinetic coefficient ( 1−day ). The K value was 0.048 and 0.75 1−day , for non-stirred

and stirred reactors, respectively.

Converti et al. (1999) compared some of the most common kinetic models for anaerobic

digestion to describe the COD (chemical oxygen demand) assumption during batch anaerobic

digestion, and indicated that the first-order model was the simplest and easiest, and the predicted

results well fitted to the experimental data. Vartak et al. (1999) conducted experiments to

determine the influence of organic loading rate and bio-augmentation on performance of an

anaerobic digester under low temperature (10 C0 ). They evaluated digester performance with

respect to biogas production based on volatile solids added.

Masse and Droste (2000) conducted a comprehensive literature review on anaerobic digestion

models and developed an improved mathematical model of anaerobic digestion in a sequencing

batch reactor process. The proposed methane flow rate was expressed as

BioiLTPCH VVQ )(4

ρΣ= (12)

where, 4CHQ is volumetric methane flow rate ( /L day ), TPV is volume of one mole of gas, LV is

volume of liquid in the reactor (L), and Bioi )( ρΣ is the methane variation caused by biological

activity ( / )g L .

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Axaopoulos (2001) predicted daily methane production rate for a solar-heated anaerobic digester

by solving Eqs. (3), (4), and (5). The predicted and measured values agreed well over the entire

10 days experimental period.

Scott and Minott (2002) developed a moving coordinate model that yields total gas production

for a plug-flow digester, and is expressed as

[ ]0

0 ),(5.0T

TVtxCC

HRTBG a

T ⋅⋅−⋅= (13)

where, BG is biogas production per day (kg/day), HRT is hydraulic retention time (days), 0C is

influent total volatile solids ( 3/ mkg ) ( TSC ⋅= 863.00 ), ),( txCT is total substrate degradation in

the digester ( 3/ mkg ), V is digester volume (m3), aT is 273.2 K, and 0T is constant temperature at

which the digester is operated. The total substrate degradation, ),( txCT , is determined from

( 1/ )( / ) ( / )0

2( , ) {( 2 )[1 ] [1 ]}m m

Ku t K u t K

T m mm

C KeC x t V u v k e t vu e

u V t

−− −= − − + +

⋅ ⋅ (14)

where, K is Hashimoto's ideal plug flow constant (1.26), mu is bacterial growth rate and is

determined by equation (5), v is daily flow rate of manure slurry into the digester ( daym /3 ), and

t is maximum HRT for digestion up to a given point (days).

Harikishan and Sung (2003) evaluated the performance of temperature-phased anaerobic

digestion (TPAD) process in digestion of livestock waste, and investigated the applicability of

the TPAD process in the stabilization of dairy cattle manure. Methane production with respect to

VS reduction resulted in 0.52-0.62 4 /L CH gVS destroyed for organic loading rates of 1.87 -

5.82 /( )g VS L day− .

Keshtkar et al. (2003) developed a mathematical model for anaerobic digestion to describe the

dynamic behavior of non-ideal mixing continuous flow reactors. The microbial kinetic model

included an enzymatic hydrolysis step and four microbial growth steps, together with the effects

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of substrate inhibition, pH, and thermodynamics considerations. They concluded that methane

yield was strongly dependent on pH of the reactor and increased with greater HRTs.

McGrath and Mason (2004) developed a method for assessing biogas production based on visual

monitoring of biogas evolution events (size and frequency of gas occurring at the pond surface)

in an anaerobic waste stabilization pond, and then applied the method to anaerobic ponds that

treat farm dairy wastewater.

Karim et al. (2005) operated six laboratory-scale biogas mixed anaerobic digesters to study the

effect of biogas recycling rates and draft tube height on performance. They found higher

methane production rate in unmixed digesters, and increased biogas circulation rate reduced

methane production. No difference in methane production rate was observed with varying draft

tube height.

Blumensaat and Keller (2005) developed a process model to simulate the dynamic behavior of a

pilot-scale process for anaerobic two-stage digestion of sewage sludge. This process model

concept was a derivative of the International Water Association (IWA) Anaerobic Digestion

Model No.1 (ADM1) that had been developed by IWA task group. They did several

modifications to the original ADM1 model concept to allow an application for the pilot-scale

digestion process, and calibrated the model for a two-stage thermophilic/mesophilic process

configuration and municipal sewage sludge with typical characteristics as substrate input.

Model Development

Biogas production in an anaerobic digester is a chemical reaction process, which is governed by

mass and momentum conservations, turbulence, energy balance, species transport, and chemical

reactions. Because anaerobic digestion is dependent on process flow parameters and

temperatures, prediction of temperature and flow variables is an important component that

cannot often be neglected by assume bulk conditions prevail. This model was developed based

on the following assumptions:

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• Heat flow and species transport through the digester are 3-D steady state.

• The model is limited to plug-flow anaerobic digesters where fluid flow is very low.

Thus, momentum and turbulence are considered to be negligible.

• The digester cover, walls, and floor are adiabatic.

• The liquid manure is assumed to be Newtonian fluid.

• The manure temperature is constant at 32 C0 before species reaction.

• Species reaction takes place only in one step, i.e., reactants can be directly converted into

products without intermediate products.

• The percentage remaining of reactant ( 6126 OHC ) is 80% after reaction.

• Biogas production doesn’t affect the transport of manure as it rises to the surface.

Mass Conservation Equation

The equation for conservation of mass, or continuity equation, is expressed as

( ) 0=∂

∂+∂∂

ii

uxt

ρρ (15)

where, t is time, ρ is density of mixture, and iu (and ju shown in the equation below) is

velocity in tense form.

Energy Equation

The energy equation is of the form (Patankar, 1980):

( ) ( )( ) ( ) hj

effijjjji

effi

ii

SuJhx

Tk

xpEu

xE

t+

+−

∂∂

∂∂=+

∂∂+

∂∂ ∑ τρρ

r (16)

where, effk is the effective conductivity, and jJr

is diffusion flux of species j, jh is sensible

enthalpy of species j. The first three terms on the right-hand side of Eq. (16) represent energy

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transfer due to conduction, species diffusion, and viscous dissipation, respectively. Sh includes

heat of chemical reaction and any other volumetric heat sources.

In Eq. (16)

2

2iup

hE +−=ρ

(17)

where, h is sensible enthalpy, and is defined for ideal gases as

jj

j hYh ∑= (18)

and for incompressible flows as

ρp

hYh jj

j += ∑ (19)

jY is mass fraction of species j and

∫=T

T jpjref

dTch, (20)

where, refT is 298.15 K.

Sources of energy, Sh, in Eq.(16) includes the source of energy due to chemical reaction,

expressed as

jj

T

T jpj

jreactionh RdTc

Y

hS

ref

jref∑ ∫

+=

,,

0

, (21)

where, 0jh is formation enthalpy of species j at the reference temperature

jrefT , , and Rj is

volumetric rate of creation of species j.

Species Transport Equations

The species transport equations in liquid manure can be written in general form as (Patankar,

1980):

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iii

iii

j RJx

Yux

Yt

+∂∂=

∂∂+

∂∂ r

)()( ρρ (22)

where, iY is mass fraction of each species, iR is reaction rate (rate of production of species i),

and iJr

is diffusion flux of species i due to concentration gradients.

For mass diffusion in laminar flow, iJr

is computed as

i

imii x

YDJ

∂∂

= ,ρr

(23)

where, miD , is diffusion coefficient for species i in the mixture.

Chemical Reaction Equations

The initial conversion of raw waste to soluble organics can be expressed as (Chang, 2004): ++ +→++ 4612625136 HNOHCHOHNOHC (24)

In this study, the methane production was simplified by converting 6126 OHC into 4CH and 2CO

through chemical reaction, Eq. (1) (Buswell and Mueller, 1962). By substituting 6=n , 12=a ,

and 6=b into Eq. (1), the chemical reaction of 6126 OHC results in

426126 33 CHCOOHC += (25)

There are three species in the mixture. One species, 1Y , represents the reactant 6126 OHC and the

other two species, 2Y , and 3Y , represent the simplified biogas products, 2CO and 4CH ,

respectively.

Modeling Reaction Rate

The reaction rate can be computed either by Arrhenius rate expressions or by using the eddy-

dissipation concept of Magnussen and Hjertager (1976). The reaction rate is computed using the

Arrhenius expression as

∑=

=RN

rriiwi RMR

1,,

ˆ (26)

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where, iR is reaction rate, iwM , is molecular weight of species i, RN is number of chemical

species in reaction r, riR ,ˆ is molar rate of creation or destruction of species i in reaction r, which

is calculated as

)][)((ˆ1

,,',

'',,

',∏

=

−=r

rj

N

jrjrfririri CkR

ηνν (27)

where, ',riν is stoichiometric coefficient for reactant i in reaction r, ''

,riν is stoichiometric

coefficient for product i in reaction r, rjC , is molar concentration of each reactant and product j

in reaction r, ',rjη is forward rate exponent for each reactant and product j in reaction r, and rfk ,

is forward rate constant for reaction r.

For an eddy-dissipation model that deals with turbulence-chemistry interaction, iR is given by

the smaller of the two expressions given below:

=

RwrR

R

Riwrii M

Y

kAMR

,'

,,

', min

νερν (28)

∑∑= N

j jwrj

P Piwrii

M

Y

kBAMR

,'',

,', ν

ερν (29)

where, PY is mass fraction of any product species P, RY is mass fraction of a particular reactant

R, A is an empirical constant equal to 4.0, B is an empirical constant equal to 0.5, jwM , is

molecular weight for each reactant and product j, RwM , is molecular weight of reactant R,

'',rjν is stoichiometric coefficient for each reactant and product j in reaction r, and N is total

number of chemical species in reaction.

For mixing flow anaerobic digesters, Eqs. (28) and (29) are used to calculate the reaction rate

because the flow in the digester is turbulent resulting from active mixing. For plug-flow

anaerobic digesters, where liquid manure flow is laminar, rfk , was computed by using first-order

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BOD removal rate for an ideal plug-flow reactor (Metcalf and Eddy, 2003) because information

on rfk , is lacking in the literature. The rate value for the chemical reaction, in Eq. (25), is

calculated as

)exp( ,0

τ⋅−= rfkC

C (30)

where, 0C

C is percentage remaining of 6126 OHC , and τ is hydraulic retention time.

For plug flow digesters manure velocities are low and the hydraulic retention time,τ , can be

calculated as

v

L=τ (31)

where, L is digester length, and v is velocity of liquid manure, which can be calculated as

A

Vv

&= (32)

where, V& is volumetric flow rate of manure slurry into digester, and A is influent area. For

example, if 0C

C = 80%, then )(1021.6 18,

−−×= sk rf .

CFD Simulation

The commercial CFD software, Fluent 6.1 (Fluent Inc., 2005), is used to model biogas

production from a plug-flow digester. The mesh of digester geometry is generated by Gambit

Software (Fluent, 2005) using structured grids. The mesh volumes of the computational domain

occupied by fluid (liquid manure) inside digester was 31,480 tetrahedron grids. The modeling

procedure includes the following steps:

(1) Verify and smooth the grid.

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(2) Define models by solving the 3-D, steady state, implicit, and segregated model for the

continuity, energy, and species transport equations. Models include volumetric reactions,

diffusion energy source and finite-rate/eddy-dissipation.

(3) Define material properties for 6126 OHC , 4CH and 2CO .

(4) Define boundary conditions by setting heat flux to zero at all solid walls, setting velocity,

temperature, and the species mass fraction of 6126 OHC at inlet as 1.1×10-5 m/s, 305 K,

and 1, respectively, and setting fully-developed flow at outlet.

(5) Anaerobic digestion reaction rates are defined in a user model.

(6) Define operational conditions by activating the gravitational acceleration and keeping all

other default numbers.

Solve the governing equations (15), (16), and (22) by activating energy and species equations

without flow and turbulence equations, since the fluid (liquid manure) flows at low velocity in

plug flow digesters. The first order upwind scheme is used to discretize the governing equations,

which can be solved by SIMPLE (semi-implicit method for pressure-linked equations) algorithm

(Patankar, 1980).

Model Validation

In this study, the model predictions were validated using experimental data published by

Gebremedhin et al. (2004). The digester dimensions, daily manure flow rate, hydraulic retention

time and ambient temperature used in the simulations, and the measured (Gebremedhin et.al.,

2004) biogas production are given in Table 1. The percentage of methane in the biogas is

assumed to be 60%, and its density to be 0.6679 3/ mkg . The predicted biogas, 1207 daym /3 , is

within 5% of measured value, 1274 daym /3 , as shown in Table 1. In the simulation,

convergence occurred after 350 iterations (Figure 2). The convergence criteria were set to be: (1)

that residuals of species is < 3101 −× , and (2) that residual of energy is < 5101 −× . The

calculation trend was steady and without any fluctuations.

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In this study, the momentum equations and turbulent model are not considered in calculating

biogas predictions because flow velocity of liquid manure in the digester is very low. The

prediction calculations are based on the principles of mass conservation, energy, and species

transport. For this reason, there are only three curves shown in Figure 2 – one for energy, and

two for species transport. The two species are 6126 OHC and 2CO . The sum of mass fractions of

all species is equal to one. For example, if there are N species in the chemical reaction, the Nth

mass fraction is determined by [ ∑−

=

−1

11

N

iiY ]. In this simulation, N =3 since there are only three

species ( 6126 OHC , 2CO , and 4CH ), where 4CH is set as the Nth (3rd) species.

The range of molar concentrations for the three species, 6126 OHC , 4CH and 2CO , are:

51067.2 −× - 21080.3 −× , 61072.8 −× - 41072.1 −× , and 31089.1 −× - 21091.3 −× kmol/m3,

respectively. The simulated contours of the molar concentrations for the three species are given

in Figures. 3, 4, and 5.

From Fig. 3, it can be observed that the concentration of the organic material ( 6126 OHC ) is high

close to the inlet, and low far from the inlet. The concentration also remained unchanged after a

certain distance (about one-sixth of length) from the inlet. The reason is that chemical reaction

gradually develops from the inlet to the outlet. From Figs. 4 and 5, it is evident that the

distributions of 4CH concentrations and 2CO concentrations are similar. However, the actual

values of 4CH is higher than that of 2CO because CH4 is the main product of the chemical

reaction. Similarly, the concentrations of 4CH and 2CO increased gradually from the inlet to

one-sixth the length and then remained unchanged up to the outlet.

The temperature profile within the digester is given in Fig. 6. The inlet temperature is 305K

(32 C0 ), which is the assumed boundary condition temperature, and the outlet temperature is 311

K (38 C0 ). Temperature profile exists because of chemical reaction taking place when the

reactants (organic material and water) are mixing.

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Conclusions The following conclusions can be drawn from the study:

(1) A comprehensive literature review on modeling biogas production from anaerobic digestion

was conducted.

(2) A general three-dimensional numerical simulation model that predicts biogas production

from plug-flow type digesters is developed. The model is based on the principles of mass

conservation, energy balance, species transport, and chemical reactions.

(3) Model prediction for a plug-flow anaerobic digester is validated against experimental data

obtained from the literature. The results agree within 5%.

19

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24

Table 1. Input information and comparison of measured and predicted results1.

Digester dimension

Measured biogas

production

(m3/day)

Simulated

biogas

production

( daym /3 )

Error

(%)

Length

(m)

Width

(m)

Depth

(m)

39.62

9.44

4.26

1274

1207

5.25

1Measured biogas production is from AA Dairy Farm, Homer, NY (Gebremedhin et al., 2004)

Daily manure flow rate =38.336 m3/day

HRT = 3590906 s (41 days and 13 hrs)

Retention temperature = 32 C0

25

measured 1274

simulated 1207

0

200

400

600

800

1000

1200

1400

Bio

gas

prod

uctio

n (m

^3/d

ay)

Figure 1. Comparison of measured and simulated biogas.

26

Figure 2. Residuals versus iterations in the simulation cycles.

27

Figure 3. Contours of simulated molar concentration of 6126 OHC (kmol/m3).

Figure 4. Contours of simulated molar concentration of 2OC (kmol/m3).

28

Figure 5. Contours of simulated molar concentration of 4HC (kmol/m3).

29

Figure 6. Contours of simulated static temperature inside the digester (K).