CFD studies on biomass gasification in a pilotscale dual fluidizedbed system

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CFD studies on biomass gasification in a pilot-scale
dual fluidized-bed system
Hui Liu, Robert J. Cattolica*, Reinhard Seiser
Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Drive, La
Jolla, CA, 92093, USA

article info

abstract

Article history:

A comprehensive CFD (Computational Fluid Dynamics) model using the MP-PIC (Multi-

Received 21 December 2015

phase Particle-In-Cell) method was developed to simulate a pilot-scale (6 tons/day, 1 MW

Received in revised form

th) dual fluidized-bed biomass gasification system. In this model the particulate phase was

2 April 2016

described with the blended acceleration model. The momentum, mass, and energy

Accepted 28 April 2016

transport equations were integrated with the kinetics of heterogeneous biomass and char

Available online xxx

reactions and homogeneous gas-phase reactions to predict the particle circulation, producer gas composition, and reactor temperature. The simulation results were compared

Keywords:

with experimental data from the pilot-scale gasification system to validate the model at

Biomass

different operating conditions. Parametric studies were conducted to investigate the

Gasification

impact of gasifier temperature, steam to biomass ratio (S/B), and air supply to the

Fluidization

combustor on the producer gas composition. The studies showed that increasing gasifier

Circulation rate

temperature and steam to biomass ratio (S/B) promoted syngas (CO þ H2) production and

CFD

increased hydrogen content in producer gas. The effect of air supply was minor, because

Pilot-scale

for the dual fluidized-bed system air was not directly involved in biomass gasification.
© 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Introduction
Currently, energy and chemical industries rely primarily on
fossil fuels. Hydrogen as a clean energy source with the high
energy density can become an alternative to fossil fuels [1,2];
however, the current hydrogen production also depends on
fossil fuels and most of hydrogen is produced from natural gas
reforming and coal gasification [3,4].
Biomass as a renewable energy source can be used to
produce hydrogen through biomass gasification [5,6]. Two
types of technologies such as fixed-bed and fluidized-bed are
mainly used for biomass gasification. Fixed-bed biomass
gasifiers are mostly preferable for small-scale syngas

production with regard to the simple process and low capital
investment [7]; however, due to the insufficient gas-particle
contact, biomass gasification process in fixed bed reactors is
slow and the tar content in the producer gas is relatively high
[8e10]. Therefore, fixed-bed gasifiers are not suitable for largescale syngas production and are only preferable for small size
plants with the capacity of up to 1.5 MW th; comparatively, the
capacities of atmospheric bubbling fluidized-bed gasifiers can
be up to 25 MW th [11]. In addition, fluidized-bed gasifiers

demonstrate good tolerance to particle sizes. The gasesolid
mixing is more efficient and less tar is generated in fluidizedbed gasifiers [12,13].
In a conventional single-reactor fluidized-bed gasifier, air
and biomass are fed to the same reactor (gasifier) which has

* Corresponding author. Tel.: þ1 858 5342984.
E-mail address: (R.J. Cattolica).
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some disadvantages. After the oxygen gas in air is consumed,
the remaining nitrogen gas in air mixes with producer gas and
dramatically dilutes the producer gas concentration. Consequently, the heating value of producer gas generated in such a
single-reactor fluidized-bed systems is low [14,15].
This issue can be eliminated by the use of a dual fluidizedbed gasification system. As shown in Fig. 1, a dual fluidizedbed system generally consists of two reactors: a fluidizedbed gasifier and a fluidized-bed combustor. In the process
biomass and steam are fed to the gasifier while air is only
supplied to the combustor. Char is generated from biomass
pyrolysis in the gasifier. Char is entrained by the bed material
and is delivered from the gasifier to the combustor. Char reacts with air in the combustor to release heat. The combustion
heat is absorbed by the bed material and is returned to the
gasifier through the bed material circulation within the dual
fluidized-bed system. Since air is only present in the
combustor and the combustor is separated from the gasifier,
the producer gas in the gasifier is free of nitrogen. Accordingly,
the producer gas in dual fluidized-bed systems will have a
higher heating value than the producer gas generated in a

single-reactor fluidized-bed system.
The dual fluidized-bed system as depicted in Fig. 1 contains
a gasifier and a combustor. These two reactors can be either a
bubbling fluidized-bed (BFB) or a pneumatic transport bed/
riser reactor. There are mainly four configurations of dual
fluidized-bed gasifiers: a BFB gasifier and a BFB combustor, a
BFB gasifier and a riser-combustor, a riser-gasifier and a BFB
combustor, and a riser-gasifier and a riser-combustor [16]. A
dual fluidized-bed system with a riser-gasifier and a risercombustor was used to gasify waste and biomass in 1970s. A
dual fluidized-bed system with a BFB gasifier and a risercombustor was developed in 1990s and a biomass gasification plant using this technology was built and has operated in
Austria since 2002 [17,18]. A dual fluidized-bed system with a
riser-gasifier and a BFB combustor was adopted by Ebara Co.,
Ltd. in 2003 [19]. Among these configurations, the combination
of BFB gasifier and riser combustor was considered to be
optimal for large-scale biomass gasification with regard to
efficient particle circulation, high fuel conversion, and low tar
generation [20].

Fig. 1 e Schematic of dual fluidized-bed gasifier.

The design and scale-up of dual fluidized-bed gasifiers are
challenging and have in the past depended on empirical
scaling formulas, especially for dual fluidized-bed gasifiers.
The interaction between reactors and cyclone separators requires sophisticated analysis [15,21]. In recent years, CFD
(computational fluid dynamics) has proved to be a powerful
tool for the simulation of gas-particle system and numerous
CFD models were developed to simulate fluidized-bed reactors
[22e25]. Currently, three main methods have been applied for
the CFD modeling of fluidized-bed gasifiers: the EulerianeEulerian (EE) approach, the EulerianeLagrangian (EL)
approach, and the hybrid EulerianeLagrangian approach.

Compared with the EE and EL approaches, the Multiphase
Particle-In-Cell (MP-PIC) method as a hybrid EulerianeLagrangian approach can provide both the required accuracy and efficiency. The MP-PIC method was initially
developed by Harlow et al. [26] for single-phase flows and then
was improved significantly by O'Rourke et al. [27] for multiphase flows. In the MP-PIC method an isotropic stress term is
applied in the particle acceleration equation to calculate particle interactions. Since this solid stress term is defined by a
function of solid volume fraction, the trajectory of each particle is not needed, which saves the computation time
significantly. Therefore, the MP-PIC method is a
computational-efficient method and can also be applied to
simulate dense phase flows [28,29].
For the EE approach, particle sizes in a particulate phase
must be set to the same value. In contrast, particles in the MPPIC method can have different diameters by the use of particle
size distribution function (PSD). Additionally, the calculations
of momentum, mass, and energy transfer for the particulate
phase in the MP-PIC method are implemented on individual
particles or numerical particle parcels. Thus, if there are solidegas reactions occurring on particles, each particle size can
change in accordance with solid species generation or consumption by the reactions.
Shi et al. [30] established a hydrodynamic model using the
MP-PIC method to investigate the effect of particle size. Two
size distribution functions, the Gaussian and Lognormal size
distributions, were applied to simulate the particulate phase
in a circulating fluidized-bed (CFB) riser. The study showed
that the PSDs had significant impact on the flow pattern in the
lower region of the riser. Wang et al. [31] developed another
hydrodynamic MP-PIC model to study a binary PSD case and a
polydisperse case. The predicted flow pattern and particle
velocity in both of cases showed good agreement with
experimental data.
In comparison with the EL approach that can be only
applied to simulate small-scale fluidized-bed systems, the
MP-PIC method is capable of simulating the full-loop of largescale fluidized-bed gasifiers. Wang et al. [32] built a hydrodynamic MP-PIC model to simulate the full-loop of a CFB system

including a riser, a cyclone separator, and a loop-seal. Their
model successfully predicted the particle circulation and the
pressure distribution in the full-loop of CFB system. Jiang et al.
[33] also conducted a hydrodynamic study to simulate the fullloop of a CFB system including a riser, six cyclone separators,
and six loop-seals. The predicted solid circulation, pressure,
and velocity profiles were validated with experimental data.
As shown above, the MP-PIC models are capable of presenting

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more practical and valuable information for the design and
scale up of fluidized-bed gasifiers than the EL approach.
Previous models were primarily developed for hydrodynamic studies without considering chemical reactions and
were mainly focused on single-reactor fluidized-bed systems.
A complete CFD model of biomass gasification in a dual
fluidized-bed system including reaction kinetics is rarely seen.
Additionally, previous analyses of the single-reactor systems
can't be applied directly to the dual fluidized-bed systems,
considering the significant difference in the configurations of
two fluidized-bed systems. It is necessary to develop a CFD
model of dual fluidized-bed gasifier to facilitate the design and
scale-up of such gasifiers.
In this work, a three-dimensional CFD model using the
MP-PIC method is built to simulate a pilot-scale dual
fluidized-bed biomass gasifier with the capacity of 6 tons/day
and 1 MW th. This simulated dual fluidized-bed system includes a BFB gasifier, a riser-combustor, a cyclone separator,
and a loop-seal. In this model, the gas phase is described by
the Large Eddy Simulation (LES) while the particulate phase

is described by the blended particle acceleration equation.
The momentum, mass, and energy transport equations are
integrated with the kinetics of gasesolid and gasegas reactions to simulate biomass gasification in the dual
fluidized-bed system. The simulation results such as producer gas composition and reactor temperature are
compared with experimental data to validate the model at
different operating conditions. The effects of important
operating parameters such as gasifier temperature, steam to
biomass ratio, and air supply to the combustor are also
analyzed in this work.

ffiffiffiffi
p
3
V

D¼

(7)

The species transport equations is shown as follows:


v ag rg Yn
vt


a m


g

þ V$ ag rg ug Yn ¼ V$
VYn þ dmn; react:
Sc

The energy transport equation is applied to solve for the
temperature of the gas phase, as shown below:


v ag rg E
vt

keddy ¼



À À
vp
þ V$ ag rg ug E ¼ ag þ ag ug $Vp À V ag kmol
vt
Á
Á
þ keddy VTg þ Sinter þ qdiff þ Q

Cp meddy
Prt

The dual fluidized-bed gasification system contains two types
of particles, biomass and bed material. The solid movement
and solid mixing in the binary-particle system are described
by the blended particle acceleration equation. The equation is

shown as follows [35]:
À
Á Vp
dup
up À up
¼ Dp ug À up À
þXþgþ
rp
dt
2tD

The continuity equation and the momentum transport
equation for the gas phase are as follows:

h¼



v ag rg ug
vt



þ V$ ag rg ug ug ¼ ÀVp þ F þ ag rg g þ V$tg

(10)

Particulate phase

1

16 as s
¼ pffiffiffiffiffiffi
g0 ðas Þhð1 À hÞ
tD
3p r32



þ V$ ag rg ug ¼ dmp

(9)

where Sinter is the energy exchange between the gas and particulate phases, qdiff is the enthalpy diffusion, and Q is the
energy source by chemical reactions.

Gas phase

vt

(8)

(11)

where X is the modified acceleration due to the contact force
between particles. tD is the damping time due to inelastic
particle collisions and is defined as follows:

Governing equations




v ag rg

3

(1)

(2)

1 þ ep
2

s2 ¼

À
Á2
1
∭ fm up À up dmp dup dTp
rp as

as ¼ ∭ f

(12)

(13)

(14)

m
dmp dup dTp

rp

(15)

where dmp is the mass production from the gasesolid reactions, tg is the stress tensor of the gas phase and is calculated using the following equations [34]:

rp ¼

1
∭ fmup dmp dup dTp
as

(16)


vu
 vu

vug;j
2
g;i
k
m þ meddy dij
þ
À
tg ¼ mlam þ meddy
3 lam
vxj
vxi
vxk

(3)

up ¼

1
∭ fmup dmp dup dTp
rp as

(17)

 
meddy ¼ Crg D2 S

(4)

g0 ðas Þ ¼

  qffiffiffiffiffiffiffiffiffiffiffiffiffiffi
S ¼ 2Sij Sij

(5)

r32 ¼

(6)

where s is the mass-weighted particle velocity variance, r32 is
the Sauter mean radius, g0(as) is the radial distribution

Sij ¼



1 vui vuj
þ
2 vxj vxi

as;cp
as;cp À as

(18)

∭ fr3 dmp dup dTp
∭ fr2 dmp dup dTp

(19)

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function, and ep is the particleeparticle restitution coefficient.X is defined in the following equations:

Reaction kinetics

"
À

Á
À
Á
1 vtp
~p À D ug À u
~p À
X¼À
þ g1 ðas Þ D ug À u
rp as vxi

In this dual fluidized-bed system, after biomass is fed to the
gasifier, moisture is released from biomass and then biomass
is decomposed into char, volatile gases and ash. Some char
remains in the gasifier to react with gases while the rest of
char is transported to the combustor to react with O2 to
release heat. In this model the heterogeneous reactions such
as biomass drying, pyrolysis, and char gasification and combustion are included. The homogeneous gas-phase reactions
including the water gas shift reaction, steam reforming reaction, and gas oxidation reactions are also included.
The heterogeneous reactions are defined as discrete particle reactions. In this model the calculations of heterogeneous reactions are implemented on each numerical particle.
Each numerical particle can have its own size, temperature,
and solid species. Note that in this model all of heterogeneous
and homogeneous reactions are described with global reaction schemes, and detailed reaction mechanisms are not used.
It is well-known that detailed reaction kinetics can provide
much more accurate predictions than global reaction kinetics;
however, detailed reaction kinetics require intense computation. For example, as reported by Titova et al. [37], the detailed
reaction kinetics of propane combustion required 599 reaction
steps and 92 species. For a gasification model involving both
heterogeneous and homogeneous reactions, thousands of
elementary reactions may be required. Considering the unaffordable computation cost of detailed reaction schemes,
global reaction schemes were adopted for the CFD modeling of

biomass gasification [23,38e41].

1
1
À
rp rp

!

vp
vxi

#

(20)
10Ps abp
ÂÀ
Á À
ÁÃ
max acp À ap ; ε 1 À ap

tp ¼

&
g1 ðas Þ ¼

D¼

(21)

0 if as ¼ 0
1 if as ¼ as;cp

(22)

∭ fmDdmp dup dTp
rp as

(23)

∭ fmDup dmp dup dTp
rp as D

(24)

~p ¼
u

where tp is the isotropic solid contact stress, Ps, b, and ε are the
model constants, g1(as) is the blending function, D is the
~p is the drag-averaged
average particle drag coefficient, and u
particle velocity.
The interphase momentum transfer, F, is defined by:
#
)
( "
À
Á Vp
dmp

þ up
dmp dup dTp
F ¼ ∭ f mp Dp ug À up À
rp
dt

(25)

The drag coefficient, Dp, is described as follows [36]:
6 rgjug Àup j
Dp ¼ Cd
rp dp
8

(26)

Biomass drying
8
>
>
>
>
>
>
<

24agÀ2:65
Re

The biomass drying rate is described in the following Arrhenius equation [42]:

; Re < 0:5

À
Á
Cd ¼ 24aÀ2:65
g
>
1 þ 0:15Re0:687 ; 0:5 Re
>
>
Re
>
>
>
:
; Re > 1000
0:44aÀ2:65
g

1000

(27)

dmp
dmp dup dTp
dt

(28)

(29)

dmp;n ag Mwp;n dCp;n
¼
mp
dt
rp ap
dt

(30)

Á
dTp
1 kd Nu À
¼
Ap Tg À Tp
mp dp
dt

where Cp,n is the concentration of solid species n.

Biomass pyrolysis
The one-step global-reaction scheme is used to simulate
biomass pyrolysis in which biomass is decomposed into volatile gases and char. In the experiments tar content was less
than 2% of mass fraction due to the high gasifier temperature
of 850 C. In this model tar is not included and is assumed to be
fully converted to non-condensable gases for simplicity.
Biomass pyrolysis is modeled as follows:
Biomass/a1 CO þ a2 CO2 þ a3 H2 þ a4 CH4 þ a5 C2 H4 þ a6 C2 H6

N
dmp X
dmp;n
¼
dt
dt
i¼1

CV

R (1)

where mbio is the mass of biomass.

Since the MP-PIC method is a Lagrangian-based method,
mass transfer and energy transfer in the model are calculated
on the basis of numerical particles. Note that in the MP-PIC
method a numerical particle represents a cluster of real particles to simplify the computation.
The mass and energy transport equations for the particulate phase are:
dmp ¼ À∭ f



À10585
mbio
r1 ¼ 5:13 Â 1010 exp
Tp

þ a7 Char
R (2)

(31)

Various methods can be applied to determine the values of
stoichiometric coefficients. One method is to assign the coefficient values of pyrolysis products based on pyrolysis
experimental results [43,44]. The advantage of this method is
that all of the coefficient values are directly from experimental
measurements. However, in such a pyrolysis experiment the
heating rate is generally much slower than the heating rate of

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pyrolysis in a gasifier where both of biomass pyrolysis and
combustion occur. Since biomass pyrolysis is dramatically
influenced by the heating rate, the product composition from
slow pyrolysis may not be the same as the product composition of fast pyrolysis in a gasifier [45e47]. Additionally, in
Reaction-2, on the left (reactant) side the contents of C, H, and
O in biomass were determined in the ultimate analysis while
on the right (product) side the contents of these elements were
measured in the pyrolysis experiment. Since these contents
were measured in two different experiment using different
methods, the contents of C, H, and O in the reactant may not
be the same as those in the products in Reaction-2. Therefore,
the elemental balance may not be strictly followed in this
pyrolysis modeling approach.
In this model another method is used to calculate the coefficients to achieve better elemental mass balances. The
values of a1 a2, a3, and a7 for the major species, CO, CO2, H2,
and Char, are calculated from the proximate and ultimate

analysis data, as proposed by other researchers [48e50]. The
values of a4, a5, and a6 for the minor species such as CH4, C2H4,
and C2H6 are adjusted to fit experimental data.
C19.8166H24.524O11.8501 is defined as biomass, based on the ratios
of C/H/O in the ultimate analysis of biomass sample. The coefficient values are shown in Table 1. It is seen that the
elemental mass balances are applied. The contents of C, H,
and O in the products of biomass pyrolysis agree well with the
elements measured in the ultimate analysis of biomass. Note
that due to the strict elemental mass balances, changes in any
defined species of pyrolysis can cause changes in the coefficient values of other species. For example, if only CH4
and C2H4 are defined as minor species, rather than three
species of CH4, C2H4, and C2H6 as in the current model, the
coefficient values of other species need to change to maintain
the elemental mass balances [51].

In the dual fluidized-bed system, some char is transported
from the gasifier to the combustor and reacts with air in the
combustor to release combustion heat. Char combustion is
defined as follows [52]:

R (4)

C þ H2 O4CO þ H2

R (5)

C þ 2H2 4CH4

R (6)

The rates of the reactions are calculated in the following
equations:


À22645
½CO2 Š
r4f ¼ 1:272mc Texp
Tp

(33)



À2363
r4r ¼ 1:044 Â 10À4 mc T2 exp
À 20:92 ½COŠ2
Tp

(34)



À22645
½H2 OŠ
r5f ¼ 1:272mc Texp
Tp

(35)




À6319
À 17:29 ½H2 Š½COŠ
r5r ¼ 1:044 Â 10À4 mc T2 exp
Tp

(36)



À8078
r6f ¼ 1:368 Â 10À3 mc Texp
À 7:087 ½H2 Š
Tp

(37)



À13578
À 0:372 ½CH4 Š0:5
r6r ¼ 0:151mc T0:5 exp
Tp

(38)

The reaction kinetics were originally proposed by Syamlal
and Bissett [53] and then were adjusted by Snider et al. [54] to
suit the purpose of particle-chemistry modeling in the MP-PIC
method.

Water gas shift reaction, steam reforming reaction, and
oxidation reactions of CO, H2, CH4, C2H4, C2H6, and C3H8 are
included in this model. The kinetics of homogeneous reactions are shown in Table 2.

Experiment setup and model settings
(32)

The pre-exponential factor of 8:68 Â 106 is adjusted to fit
experimental data.

Table 1 e Pyrolysis product coefficients.

CO
CO2
H2
CH4
C2H4
C2H6
Char

C þ CO2 42CO

R (3)



À29160
½O2 Š
r3 ¼ 8:68 Â 106 ac Texp

Tp

Species

The reactions between char, CO2, H2O, and H2 are considered to be reversible reactions and are described in the forward and reverse reactions:

Homogeneous gas-phase reactions

Char combustion and gasification

C þ O2 /CO2

5

Coefficient

Value

a1
a2
a3
a4
a5
a6
a7

5.50765
3.1712
5.7076
2.1558

0.49665
0.4165
7.1556

The data used to validate the CFD model are from the operation of a pilot-scale dual fluidized-bed gasifier with the capacity of 6 tons/day and 1 MW th at Woodland Biomass
Research Center (WBRC), located in Woodland, California,
USA, as shown in Fig. 2 (a). The dimensions of the dual
fluidized-bed system are demonstrated in Fig. 2 (b).
Almond prunings were used as biomass feedstock in the
experiments and the properties of almond prunings are displayed in Table 3. As seen in Fig. 2 (c), this dual fluidized-bed
system included a gasifier, a combustor, a cyclone separator,
and a loop-seal. In the experiments biomass was discharged
constantly from a storage cart on a weight scale. Biomass was
transported by a bucket elevator to a couple of biomass hoppers and then was distributed continuously to the gasifier
with a screw conveyor. Steam was generated in a steam
generator and was superheated over 330 C in a series of heat

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Table 2 e Homogeneous reaction kinetics [55e59].
Homogeneous reactions
Water gas shift reaction
CO þ H2 O/CO2 þ H2 (R7)
Steam reforming reaction
CH4 þ H2 O/CO þ 3H2 (R8)
CO oxidation

CO þ 0:5O2 /CO2 (R9)
H2 oxidation
H2 þ 0:5O2 /H2 O (R10)
CH4 oxidation
CH4 þ 2O2 /CO2 þ 2H2 O (R11)
C2H4 oxidation
C2 H4 þ 3O2 /2CO2 þ 2H2 O (R12)
C2H6 oxidation
C2 H6 þ 3:5O2 /2CO2 þ 3H2 O (R13)
C3H8 oxidation
C3 H8 þ 5O2 /3CO2 þ 4H2 O (R14)


r7 ¼ 2:75as exp


À10079
Tg

½COŠ½H2 OŠ

the pre-exponential
factor, 2.75,

 is adjusted to fit experimental data

½CH4 Šþ½H2 OŠ
r8 ¼ 720as exp À9057
2½H2 Šþ½COŠ
Tg

the pre-exponential
 720, is adjusted to fit experimental data
 factor,
½COŠ½O2 Š0:25 ½H2 OŠ0:5
r9 ¼ 1:28 Â 1017 exp À34761
Tg


r10 ¼ 1:0 Â 1014 exp À5052
½H2 Š½O2 Š
Tg


½CH4 Š0:7 ½O2 Š0:8
r11 ¼ 5:01 Â 1011 exp À24417
Tg


r12 ¼ 1:0 Â 1015 exp À20808
½C2 H4 Š½O2 Š
Tg


½C2 H6 Š0:5 ½O2 Š1:25
r13 ¼ 4:4 Â 1011 exp À15199
Tg


r14 ¼ 8:6 Â 1011 exp À15000
½C3 H8 Š0:1 ½O2 Š1:65

Tg

Fig. 2 e (a): Dual fluidized-bed gasifier at WBRC. (b): Dimensions of dual fluidized-bed. (c): Flow chart of biomass gasification
system. (d): Boundary conditions (BC) of CFD model.
exchangers. Then, the superheated steam was injected at the
bottom of the gasifier through six nozzles. Some of char
generated from biomass pyrolysis was transported from the
gasifier to the combustor. The air was preheated above 290 C

in a series of heat exchangers and was supplied to the
combustor at three different locations as the 1st, 2nd, and 3rd
air supplies. Char in the combustor burned with air to release
the combustion heat. Propane and an additional amount of air

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Table 3 e Proximate and ultimate analysis of biomass
feedstock.
Proximate analysis (wt. %)
Moisture
5.18

Fixed carbon
20.20

Volatile matter
72.53

Ash
2.09

Ultimate analysis (wt. %)
C
51.3

H
5.29

O
40.9

N
0.66

S
0.01

Cl
0.04

Residual
1.80

The simulation was solved with the finite volume method.
As shown in Equations (4)e(7), the subgrid-scale turbulence
model of large eddy simulation was applied to describe turbulent gas flows in the dual fluidized-bed system [61]. The
partial donor cell differencing scheme, a weighted average of
central difference and upwind scheme, was applied to calculate the face value of the variables in the transport equations.

This scheme is shown as follows [62]:
4¼

were fed to the combustor through the startup burner to
provide the additional heat to the system. The bed material
absorbed most of the combustion heat and then was transported from the combustor to the cyclone separator. The bed
material was disengaged from the flue gas in the separator
and then fell down to the loop-seal. After fluidized by the
steam in the loop-seal, the bed material was carried back to
the gasifier. In the experiments a commercial ceramic bed
material (CARBO HSP® 30/60) was used in the experiments.
Producer gas was sampled by stainless sampling lines from
the gasifier. Then, the gas was cleaned in an impinger filled
with biodiesel at 0 C and was analyzed with an Agilent 2000
Micro GC. Tar was sampled using the tar protocol according to
EU-CEN/TS 15439. The gravimetric tar was between 8 and 17 g/
Nm3, and benzene was 1500 ppm. These compounds had a
mass fraction of less than 2% and they were not included in
the model for simplicity. The error of producer gas analysis
was mainly from GC calibration process, GC measurement,
and gas sampling. In this study the overall experimental uncertainties were estimated at 10% for the major contents
including H2, CO, CO2, and CH4 and 15% for the minor contents
such as C2H4 and C2H6, as reported by Billaud et al. [60].
A 3D CFD model was built in the CFD software, Barracuda
Virtual Reactor®. The full-loop of the dual fluidized-bed system including a gasifier, a combustor, a cyclone separator, and
a loop-seal was simulated in this model. As displayed in Fig. 2
(d), a particle injection boundary condition (BC) with 25 injection points was defined as the biomass inlet. A fluid injection BC with 48 injection points was applied to simulate 6
steam nozzles in the gasifier. Note that the arrow direction of
injection BC indicated the flow direction. In the model the
steam flow was set in the downward direction, which simulated the effect of the cap of the steam nozzle. In the experiments each of steam nozzles was equipped with a cap. When

steam was introduced to the gasifier through the nozzles,
steam initially flew upwards and then was diverted and flew
downwards after encountering the caps. A fluid injection BC
with 36 injection points was used to simulate the nozzles of
the 1st air supply in the combustor. A fluid injection BC with 3
injection points was used to simulate 3 air feeding pipes as the
2nd air supply. Another injection BC with 2 injection points
was applied to simulate 2 air feeding pipes as the 3rd air
supply. Two fluid injection BCs with 6 injection points each
were defined for two steam feeding pipes in the loop-seal. The
propane supply to the combustor was defined by a mass flow
rate BC. The outlets of the gasifier and cyclone separator were
defined by two pressure outlet BCs.

7

u1 a1 A1 r1 þ u2 a2 A2 r2
2

(39)

the donor cell property:
&
Qd ¼

Q1 if 4 > 0
Q2 if 4 < 0

(40)

the acceptor cell property:
&
Qd ¼

Q1 if 4 > 0
Q2 if 4 < 0

(41)

the face property:
1
1
Q 12 ¼ Q d ð1 þ JÞ þ Qa ð1 À JÞ
2
2

(42)

J ¼ a þ bC

(43)

C¼

2Dtj4j
a1 V1 þ a2 V2

(44)

where a and b are model constants and are defined as 0.2 and

1.0, respectively.
The no-slip boundary condition was applied at walls for
the gas phase while the partial-slip boundary condition was
implemented for the particulate phase. The time-step size
was between 1 Â 10À3 and 1 Â 10À5 s and was automatically
controlled by the CFL value (Courant-Friedrichs-Lewy
Scheme) and the maximum temperature change in a cell: if
the CFL value is lower than 0.8, the time-step size is
increased; when the CFL value is higher than 1.5, the timestep size is then decreased. Additionally, whenever the
temperature change in a cell at a time-step exceeds 300 K,
the time-step size also decreases. Orthogonal structured
grids were generated in Barracuda Virtual Reactor® for this
CFD model. Three computational grids with 216,972,
243,423, and 348,768 cells were compared and the grid of
243,423 cells was finally selected due to its acceptable accuracy and affordable computational cost [51]. The residuals
of the equations of volume fraction, pressure, velocity, energy were set to 10À7, 10À8, 10À7, and 10À6 as the simulation
convergence criterion.
The homogeneous gas-phase reactions were calculated
with the cell-volume averaged chemistry method and the
heterogeneous gasesolid reactions were modeled by the
discrete particle chemistry method. The simulation was performed with the accelerated GPU (graphics processing unit)
computing in a computer workstation with a GTX TITAN black
graphics card. The simulation time for each run was set as
100 s and the final solutions were averaged from 80 to 100 s,
which took about 4 days to be completed. The detailed model
settings are shown in Table 4.

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Table 4 e Model settings and operating conditions.
Biomass density (kg/m3)
Biomass mean diameter (m)
Bed material density (kg/m3)
Mean diameter of bed material particles (mm)
Particle size distribution of bed material
Standard deviation of the normal distribution
Solid volume fraction at close pack
Initial bed height (m)
Pressure at the gasifier and cyclone outlets (atm, abs.)
Case settings
The biomass feed rate (kg/h)
The steam supply to the gasifier (kg/h)
The 1st air supply to the combustor (kg/h)
The 2nd air supply to the combustor (kg/h)
The 3rd air supply to the combustor (kg/h)
The additional air supply to the combustor (kg/h)
The propane supply to the combustor (kg/h)
The steam supply to the cyclone separator (kg/h)

Results and discussion
Particle flow pattern and gas distributions in the dual
fluidized-bed system
The particle circulation in the system between 0 and 60 s is
presented in Fig. 3. In the figure, particles are fully fluidized

550

0.0057
3560
488
Normal distribution
0.146 dp
0.56
2.50
1.0
Case 1
228.04
85.32
28.89
240.68
305.63
561
14.63
78.21

Case 2
219.55
78.21
40.85
283.37
312.62
561
21.92
85.32

Case 3
243.04

64.71
26.52
238.01
322.76
561
0
64.71

and are entrained by the gases from the combustor to the
cyclone separator. The particles fall down to the loop-seal and
are fluidized by steam. Finally, particles are delivered back to
the gasifier.
It is also seen that the particles accumulate in the loop-seal
at 5 s. The accumulation of particles continues to grow in the
loop-seal and even reaches the bottom of the cyclone separator at 20 s. After that, the accumulated particles are

Fig. 3 e Particle circulation and solid build-up in the dual fluidized-bed system (Case 1).
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gradually removed from the loop-seal between 30 and 60 s and
are transported to the gasifier. The predicted accumulation of
particles in the loop-seal matches the observation during the
plant startup. It is mainly caused by the high rate of the initial
solid mass flow from the combustor to the cyclone separator
and loop-seal during startup. Initially, most of the particles in
the combustor are quickly carried outside and delivered to the
cyclone separator and loop-seal from 0 to 5 s due to the high
gas velocity in the combustor. The rate of the initial solid mass

flow is so high that the particles entrained to the loop-seal
can't be removed quickly and accumulate from 5 to 20 s.
Meanwhile, particles are continuously transported from the
gasifier to the combustor through the connection pipe; due to
the small size of the connection pipe, the solid flow rate from
the gasifier to the combustor is much smaller than the initial
solid flow rate from the combustor to the cyclone separator.
As a result of the slow incoming solid flow to the combustor,
the solid mass flow rate from the combustor to the cyclone
separator is then decreased. Accordingly, the particle accumulation in the loop-seal stops growing and the accumulated
particles are gradually removed from the loop-seal and are
delivered to the gasifier.
The sectional views of H2, CO, CO2, CH4, H2O, and O2 on the
xz (vertical) and xy (horizontal) planes in Case 1 are shown in
Fig. 4. H2, CO, and CH4 are generated in the lower left region of
the gasifier. The gases are accumulated in the bed of the
gasifier and then penetrate through the bed to reach the
freeboard region, and finally leave the gasifier at the top.
During the process, none of the volatile gases such as H2, CO,
and CH4 leak to the combustor. CO2 as a product of biomass

9

pyrolysis and char combustion is found in both the gasifier
and combustor. Meanwhile, steam is injected to the bottom
region of the gasifier through nozzles. Most of steam rises to
the freeboard region to react with other gases after permeating through the right side of the bed. A small amount of
steam escapes from the gasifier to the combustor through the
connection pipe. In comparison, O2 only appears in the
combustor to react with char and propane, and there is no O2

escaping to the gasifier. Since no air is present in the gasifier,
the producer gas in the dual fluidized-bed system is free of N2
and can have a high heating value. The low content of N2 in
the producer gas can also be beneficial for the downstream
processing by saving the cost of nitrogen gas removal in the
process of syngas purification.
The sectional views on the xy plane at the heights of 1.6,
2.0, 2.6, and 4.0 m show that the gases are unevenly distributed in the bed of the gasifier. The volatile gases such as H2,
CO, CO2, and CH4 are accumulated in the left region of the
gasifier where biomass enters; steam mainly stays in the right
region of the gasifier. The non-uniform patterns of the gas
distributions may be caused by the feeding locations of
biomass and steam in the gasifier. Biomass is fed at the left
side of the gasifier while steam is injected at the bottom
through the nozzles. The asymmetrical shape of the gasifier
makes the steam injection location closer to the right side of
the gasifier. The advantage of the right-side steam injection is
that steam can act as a sealing gas to avoid the volatile gases
escaping from the gasifier to the combustor and prevent O2
leaking from the combustor to the gasifier. For a single-reactor
fluidized-bed systems, part of the producer gas is burned so

Fig. 4 e H2, CH4, CO2, CO, H2O, and O2 distributions in the dual fluidized-bed system (Case 1). The horizontal section views
show the distributions of H2, CH4, CO2, CO, and H2O (at the heights of 1.6, 2.0, 2.6, and 4.0 m), and O2 (at the heights of 0.7,
2.2, 3.0, and 5.0 m).
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not all of the producer gas is available to be delivered to the
downstream unit for further processing which is the case for
the dual fluidized-bed system.

Simulation results
The simulation time for each test was set as 100 s and the
predicted simulation results were averaged between 80 and
100 s Fig. 5 demonstrates the producer gas composition at the
outlet of the gasifier in 100 s for Case 1. It is seen that the
concentrations of H2, CO, CO2, CH4, C2H4, and C2H6 increase
rapidly between 0 and 40 s. After that, the process reaches the
steady-state and all of gas concentrations become constant.
The similar trends are also observed in Cases 2 and 3.
In Fig. 6 (aec), Fig. 7 (aec), and Fig. 8 (aec) , the predicted gas
compositions and reactor temperatures for Cases 1e3 are
compared with three sets of experimental data. Gasifier
temperatures in the bottom region, the bed, and the upper
region were chosen for the gasifier comparison at the heights
of 0.66, 1.12, and 3.05 m. Three combustor temperatures as the
bottom, lower, and upper temperatures at the heights of 0.55,
1.83, and 6.4 m were selected for the combustor comparison.
The differences between the predicted and measured
concentrations of major contents such as H2, CO, CO2, and CH4
are 1.40%, 3.65%, 11.80%, and 2.70% in Case 1, 2.78%, 1.58%,
8.97%, and 1.83% in Case 2, and 10.63%, 3.86%, 16.67%, and
14.35% in Case 3. The differences in temperature prediction at
6 locations of the gasifier and combustor are 2.11%, 3.24%,
1.41%, 1.19%, 0.37%, and 2.86% in Case 1, 6.04%, 6.53%, 2.57%,
1.64%, 2.56%, and 4.87% in Case 2, and 5.35%, 1.54%,

2.23%,1.49%, 0.12%, and 3.20% in Case 3. As shown above, the
predicted gas compositions and the gasifier and combustor
temperatures are close to the measured values in the experiments. Large discrepancies are observed in the predictions of
C2H4, and C2H6. It is mainly because in the model only two
species, C2H4 and C2H6, are considered as minor contents, and
other content such as tar (less than 2% mass fraction) is not
included for simplicity.

Fig. 6 e (a): Gas composition comparison (Case 1). (b):
Gasifier temperature comparison (Case 1). (c): Combustor
temperature comparison (Case 1).

Effect of gasifier temperature
To understand the effect of the gasifier temperature, Case 1 as
a base case and three additional cases were investigated. The
propane flow rates were set as 0, 21.9, and 43.2 kg/s for the

0.4
0.35

Mole Fraction

0.3

H2
CO
CO2
CH4
C2H4
C2H6

0.25
0.2
0.15
0.1
0.05
0
0

20

40

60
Time (s)

80

100

Fig. 5 e Producer gas composition in 100 s (Case 1).

additional cases to generate different gasifier temperatures. In
this study the gasifier temperature is represented by the
“gasifier bed” temperature as described in the previous
section.
The influence of gasifier temperature on the producer gas
composition is demonstrated in Fig. 9 (a). The concentrations
of H2 and CO increase and the concentrations of CO2 and CH4
decrease as the gasifier temperature increases. The predicted

trends are consistent with the experimental data. The increase in temperature generally promotes the endothermic
reactions such as char and carbon dioxide reaction (R4), char
and steam reaction (R5), and steam reforming reaction (R8)
[63,64]. Therefore, when the gasifier temperature increases,
the concentrations of H2 and CO as products of Reactions-4, 5
and 8, increase and the concentrations of CO2 and CH4 as reactants of Reactions-4 and 8, decrease.
Compared with the single-reactor fluidized-bed systems,
the gas composition in this dual fluidized-bed system varies in
a relatively narrow range with gasifier temperature [65,66],

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Fig. 7 e (a): Gas composition comparison (Case 2). (b):
Gasifier temperature comparison (Case 2). (c): Combustor
temperature comparison (Case 2).

indicating that the effect of gasifier temperature on the producer gas composition in the dual fluidized-bed gasification
system is not as significant as those of the single-reactor fluidized-bed systems. In biomass gasification producer gas is
mainly generated from biomass pyrolysis, charegas reactions,
and other gas-phase reactions. As described previously, in the
current dual fluidized-bed system char is primarily transported from the gasifier to the combustor and only a portion of
char remains in the gasifier. Due to the reduced amount of
char in the gasifier, the gas production and consumption from
the charegas reactions including Reaction-4 and 5 are significantly reduced. Therefore, the impact of the gasifier temperature in this dual fluidized-bed system is less significant
than that in the single-reactor fluidized-bed systems.
As indicated previously, the main purpose of biomass
gasification is to produce hydrogen as an alternative to fossil
fuels. Therefore, the effect of gasifier temperature on CO and

H2, two important contents for hydrogen production, is also
investigated in this section.
Fig. 9 (bec) show the impact of gasifier temperature on the
net heating value (NHV) of syngas (CO þ H2) and the molar
ratio of H2/CO. It is observed that the NHV of syngas (CO þ H2)

11

Fig. 8 e (a): Gas composition comparison (Case 3). (b):
Gasifier temperature comparison (Case 3). (c): Combustor
temperature comparison (Case 3).

increases from 6570 to 7045 kJ/kg (biomass) as the gasifier
temperature increases from 802 to 929 C; meanwhile, the
molar ratio of H2/CO also increases from 1.13 to 1.20. As shown
Fig.4e9 (dee), 4.04%, 6.92%, and 15.74% of increases in gasifier
temperature result in 3.10%, 3.87%, and 7.22% of increases in
the NHV of syngas (CO þ H2). The increases in gasifier temperature also achieve 1.96%, 3.36%, and 6.28% of increases in
H2/CO. It indicates that high gasifier temperature promotes
syngas production and increases hydrogen concentration in
producer gas.

Effect of steam to biomass ratio
In this section Case 1 and three more cases are compared to
examine the effect of steam to biomass ratio (S/B) on the
producer gas composition. The predicted gas compositions
from these four cases are presented in Fig. 10 (a). It is observed
that when the steam to biomass ratio increases, H2 concentration increases and CH4 concentration decreases.
The effects of steam to biomass ratio on the NHV of syngas
(CO þ H2) and H2/CO are presented in Fig. 10 (bec). Similar to

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(d)

Fig. 9 e (a): Effect of gasifier temperature on producer gas composition. (b): Effect of gasifier temperature on NHV of CO þ H2.
(c): Effect of gasifier temperature on H2/CO. (d): NHV increase of CO þ H2. (e): Increase of H2/CO.

the effect of gasifier temperature, high ratio of steam to
biomass promotes syngas (CO þ H2) production and increases
hydrogen content in producer gas, which was also observed
by Pinto et al. [65], Franco et al. [66], and Gungor et al. [67]. In
Fig. 10 (dee), it is seen that 19.40%, 79.10%, and 138.80% of
increases in steam to biomass ratio result in 1.33%, 3.49%, and
6.36% of increases in the NHV of syngas and 0.94%, 3.48%, and
5.08% of increases in H2/CO.
On the other hand, compared with the impact of gasifier
temperature, the effect of steam to biomass ratio on syngas
production and hydrogen content is much smaller. The
similar trend was also observed by other researchers [68e71].
Generally, increasing steam can promote the reactions such
as char and steam reaction (R5), water gas shift reaction (R7),
and steam reforming reaction (R8). However, as mentioned
previously, in the dual fluidized-bed system char is mostly
transported from the gasifier to the combustor through the
solid circulation. As a result of less char remaining in the

gasifier, the gas production from the reaction of char and
steam (R5) is smaller.
In addition, as stated in Section 4.1, in the current system
steam is injected through a few nozzles at the bottom of the
gasifier. A major disadvantage of steam jet is that it can cause
channeling in fluidized-beds. As shown in Fig. 11, steam forms
a channel in the fluidized-bed of the gasifier right after it is

injected to the gasifier. Through the channel, steam can
quickly escape from the bed to the freeboard region and steam
may not have enough time to have full contact with the solids
and other gases. Consequently, the gas productions of R7 and
R8 also become smaller. Due to the lower amount of char
remaining in the gasifier and shorter residence time of steam
in the bed, the impact of steam to biomass ratio for the dual
fluidized-bed system is less significant than expected.

Effect of air supply
To examine the effect of the air supply to the combustor, two
additional cases are compared to Case 1. The primary air
supplies for Case 1 and other two cases are 28.89 kg/h,
43.34 kg/h, and 57.79 kg/h, respectively.
In Fig. 12, the concentrations of H2, CO, CO2, and CH4 from
three cases are compared. The gas compositions of three
cases are only slightly different from each other, indicating
that the air supply to the combustor has insignificant impact
on the gas composition in the gasifier. This finding is different
from the conclusion for the single-reactor fluidized-bed systems that the producer gas composition changes significantly
with air supply [72].
As indicated previously, in the dual fluidized-bed system

air is only introduced to the combustor and the combustor is

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Mole Fraction

(a)

13

0.42
0.37
H2
CO
CO2
CH4

0.32
0.27
0.22

0.17
0.12
0.07
0.3

NHV of CO+H2 (kJ/kg bio.)

(b)

0.5
0.7
Steam to Biomass Ratio

0.9

7250
7200
7150
7100
7050
7000
6950
6900
6850
6800
6750
0.3

H2/CO (Molar Ratio)

(c)

0.5
0.7
Steam to Biomass Ratio (S/B)

0.9

1.22
1.21
1.2
1.19
1.18
1.17
1.16
1.15

0.3

0.4

0.5
0.6
0.7
Steam to Biomass Ratio (S/B)

0.8

0.9

Fig. 10 e (a): Effect of steam to biomass ratio on producer gas composition. (b): Effect of steam to biomass ratio on NHV of
CO þ H2. (c): Effect of steam to biomass ratio on H2/CO. (d): NHV increase of synthesis gas (CO þ H2). (e): Increase of H2/CO.
isolated from the gasifier. Fig. 4 also confirms that O2 only
appears in the combustor and is separated from other gases in
the gasifier. So, O2 is not directly involved in biomass gasification. Increasing more air supply in the dual fluidized-bed
system will not dramatically affect producer gas composition as long as the air supply is adequate for char and propane
combustion in the combustor and the bed material circulation

within the dual fluidized-bed system. The effect of the air
supply to the combustor on syngas and hydrogen production
is also insignificant, because air is not directly used in the
gasifier.

Conclusions

Fig. 11 e Time-averaged solid volume fraction.

In this study, a three-dimensional CFD model was established
to simulate a pilot-scale dual fluidized-bed biomass gasifier
using the MP-PIC method. The CFD model was validated by
experimental data at different operating conditions and good
agreement was achieved. As predicted by the CFD model, in
the current dual fluidized-bed system no producer gas
escaped to the combustor and no air leaked to the gasifier in
the presence of steam as a sealing gas. Consequently, all of the
producer gas was free of N2 and was preserved in the gasifier
for the downstream processing.
The effect of gasifier temperature was investigated. As the
gasifier temperature increased, H2 and CO concentrations
increased, and CO2 and CH4 concentrations decreased. The

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u

V

velocity, (m/s)
computational cell volume, (m3)

Greek symbols
a
volume fraction
r
density, (kg/m3)
laminar viscosity, (m2/s)
mlam
meddy
turbulent viscosity, (m2/s)

Fig. 12 e Effect of air supply.

study also showed that high gasifier temperature promoted
syngas production and increased hydrogen content in producer gas. The similar trends were also observed in the study
of steam to biomass (S/B) ratio. However, the effect of steam to
biomass ratio was much smaller than gasifier temperature.
The effect of the air supply on producer gas composition,
syngas, and hydrogen production was minor due to the fact
that in the dual fluidized-bed system air was only supplied to
the combustor and was not directly involved in biomass
gasification.

Acknowledgments
The authors acknowledge the financial support from the
California Energy Commission Grant (CEC-PIR-14-023), West

Biofuels (CEC-AVR-15-017), and the University of California
Discovery Pilot Research and Training Program (Award
211974).

Nomenclature
Ap
Cp
CV
Dp
E
f
F
g
kd
kmol
keddy
Mw
Nu
p
Prt
Re
Sij
Sc
T

particle surface area, (m2)
specific heat at constant pressure, (kJ/(kg K))
specific heat at constant volume, (kJ/(kg K))
aerodynamic drag function
Enthalpy, (kJ/kg)

particle size distribution function
interphase force between the gas and particle phases
gravity, (m/s2)
the thermal conductivity of the particle phase, (W/
(m K))
the molecular conductivity of the gas phase, (W/(m
K))
the turbulent conductivity of the gas phase, (W/(m
K))
molecular weight, (kg/mole)
Nusselt number
pressure, (Pa)
turbulent Prandtl number
Reynolds number
Strain rate tensor
turbulent Schmidt number
Temperature, (K)

Subscripts
c
char
cp
close packing
g
gas phase
i,j
coordinate index
react
reaction
p

particle phase

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