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Computers and Chemical Engineering 36 (2012) 48– 56

Contents lists available at ScienceDirect

Computers and Chemical Engineering

j ourna l ho me pag e: w ww.elsev ier .com/ locate /compchemeng

FD simulation with experiments in a dual circulating fluidized bed gasifier

hanh D.B. Nguyena,d, Myung Won Seob, Young-Il Lima,∗, Byung-Ho Songc, Sang-Done Kimb

Lab. FACS, Department of Chemical Engineering, Hankyong National University, Anseong 456-749, South KoreaDepartment of Chemical and Biomolecular Engineering, KAIST, Daejeon 305-380, South KoreaDepartment of Chemical Engineering, Kunsan National University, Gunsan, Jeonbuk 573-701, South KoreaSchool of Chemical Engineering, Hanoi University of Science and Technology, No. 1, Dai Co Viet, Hanoi, Viet Nam

r t i c l e i n f o

rticle history:eceived 3 September 2010eceived in revised form 22 June 2011ccepted 6 July 2011vailable online 18 July 2011

a b s t r a c t

Gas and particles hydrodynamic behaviors were investigated in a pilot-scale cold-mode riser and abubbling fluidized bed gasifier by means of experiment and computational fluid dynamics (CFD).

Six different experimental sets were conducted in the cold-rig dual fluidized bed (DFB) at differentgas velocities in both the riser and the recycle chamber aeration. A two-dimensional (2D) multi-fluidEulerian model incorporating the kinetic theory of granular flows was applied to identify unsteady-statebehaviors of the fluidized bed.

eywords:ual circulating fluidized-bed (DFB) gasifierydrodynamicsolid circulation rateomputational fluid dynamics (CFD)imulationultiphase flow

The CFD model predicts well the solid circulation rate in the cold-rig DFB for all the six experimentalruns. A discrepancy between experiment and simulation is observed in the axial solid holdup along theriser. The simulation results demonstrate that the cold-bed simulation can be used to predict the solidcirculation rate for the hot-bed operation of the DFB gasifier.

© 2011 Elsevier Ltd. All rights reserved.

. Introduction

Due to the good solid/gas mixing and heat transfer character-stics, fluidized bed reactors have been widely used in chemical,etrochemical, and energy industries (Behjat, Shahhosseini, &ashemabadi, 2008; Vejahati, Mahinpey, Ellis, & Nikoo, 2009). Theuidized bed coal gasification is one of the most popular tech-ologies in the field of energy industries, since it has uniformemperature distribution, high mass and heat transfer rates (Yu,u, Zhang, & Zhang, 2007).

Recently, the dual fluidized bed (DFB) has been adopted for gasi-cation of both coal and biomass, since it produces high calorificroduct gas free of nitrogen even when air is used as a gasificationeagent (Murakami et al., 2007; Xu, Murakami, Suda, Matsuzawa,

Tani, 2006). When designing such a fluidized bed system, hydro-ynamics, heat transfer, and reaction kinetics must be taken intoccount, which have strong influence on the gasification perfor-ance. Hydrodynamic models based on the fundamental laws of

onservation of mass, momentum, energy, and species conversionave been believed to give better understanding of the fluidized

∗ Corresponding author at: Lab. FACS, RCCT, Department of Chemical Engineering,ankyong National University, Gyonggi-do, Anseong-si, Jungangno 327, 456-749orea. Tel.: +82 31 670 5207; fax: +82 31 670 5445.

E-mail address: limyi@hknu.ac.kr (Y.-I. Lim).

098-1354/$ – see front matter © 2011 Elsevier Ltd. All rights reserved.oi:10.1016/j.compchemeng.2011.07.005

beds and to be useful to enhance the process performance (Vejahatiet al., 2009).

Numerous experimental studies have been carried out to studyon hydrodynamic behaviors of fluidized bed risers, bubbling flu-idized bed (BFB), and circulating fluidized bed (CFB) gasifiers.Namkung, Kim, and Kim (1999) studied on flow regimes and axialpressure profiles in a laboratory-scale CFB riser. Goo et al. (2008)investigated hydrodynamic properties in a cold-mode DFB gasifierwith the capacity of 30 kWth.

Hydrodynamic properties such as the solid holdup and the solidcirculation rate play an important role in DFB operation. The solidcirculation rate is determined by the heat amount needed in thegasification (Pröll & Hofbauer, 2008; Shen, Gao, & Xiao, 2008). Astable circulation rate of the heat carrying particles is required toenhance the performance of the DFB gasifier. A uniform distributionof the axial solid holdup along the riser results in a stable solid circu-lation rate (Goo et al., 2008). The cold-rig of DFB is thus tested priorto hot-bed operation, since the hydrodynamic similarity betweenthe cold and hot beds is expected in the fluidized bed combustorand gasifier (Foscolo, Germanà, Jand, & Rapagnà, 2007).

The fluidized bed reactor has often been studied and developedin an empirical way despite of widespread applications of the flu-idized bed, because complex flow behavior of the gas-solid flow

makes flow modeling a challenging task (Taghipour, Ellis, & Wong,2005; Vejahati et al., 2009). The fundamental problem encoun-tered in modeling hydrodynamics of the gas–solid fluidized bedis the motion of two phases where the interface is unknown and

T.D.B. Nguyen et al. / Computers and Chem

Nomenclature

Gs solid circulation rate (kg/m2 s)Iv solid inventory (kg)k�s diffusion coefficient for granular energy (kg/m s)Kgs gas/solid momentum exchange coefficientp pressure (Pa)�P pressure drop (Pa)�P/�L pressure drop gradient (Pa/m)t time (s)Umf minimum fluidization velocity (m/s)Ut terminal velocity (m/s)Ug,b superficial gas velocity of the gasifier (m/s)Ug,r superficial gas velocity of the riser (m/s)Ug,vertical vertical aeration velocity (m/s)Ug,sc supply chamber aeration velocity (m/s)Ug,rc recycle chamber aeration velocity (m/s)v velocity (m/s)

Greek letters˛g gas volume fraction˛s solid volume fraction��m collision dissipation of energy (kg/s3 m)εss restitution coefficient� granular temperature (m2/s2)� density (kg/m3)� viscosity (kg/m/s)� stress tensor (Pa)gs transfer rate of kinetic energy (kg/s3 m)

Subscriptg gas

ts

ptdsflim(

lBest(flsbD(hspateH

s solid

ransient, and the interaction between the gas and solid is under-tood only for a limited range of conditions (Behjat et al., 2008).

With the advantage of increasing computational capacity, com-utational fluid dynamics (CFD) has been known as an advancedool in modeling hydrodynamics, and it is now considered as a stan-ard tool for the simulation of single-phase flows. However, CFD istill at the verification and validation stage for modeling multiphaseow systems such as fluidized beds. More improvements regard-

ng the flow dynamics and computational models are required toake CFD suitable for fluidized bed reactor modeling and scale-up

Taghipour et al., 2005; Vejahati et al., 2009).Several researchers have paid attention to modeling and simu-

ation of the hydrodynamic characteristics of fluidized bed systems.enyahia, Arastoopour, Knowlton, and Massah (2000) and Jiradilokt al. (2008) studied particles and gas flow behaviors in the riserection of a circulating fluidized bed using the kinetic theory forhe particulate phase. Taghipour et al. (2005) and Vejahati et al.2009) investigated the hydrodynamics of the gas–solid two-phaseows in a bubbling fluidized bed. For the simulation of binaryolid mixtures differing in particle sizes and densities in a fluidizeded, investigations of Cooper and Coronella (2005), Huilin, Yunhua,ing, Gidaspow, and Wei (2007), Huilin, Yurong, and Gidaspow

2003), and Huilin, Yurong, Gidaspow, Lidan, and Yukun (2003)ave been proposed to give better understanding of the particleize distribution in gas–solid fluidization systems using the multi-hase CFD approach. The simulation results indicated that mixing

nd segregation of the solid mixtures were strongly influenced byhe variations of the average particle diameter and mass fraction ofach particle class in the bed (Huilin, Yurong, and Gidaspow, 2003;uilin, Yurong, Gidaspow, Lidan, et al., 2003; Huilin et al., 2007).

ical Engineering 36 (2012) 48– 56 49

Dealing with gas–solid hydrodynamics, two differentapproaches have been taken to apply CFD modeling to thegas–solid fluidized beds: (1) Eulerian–Lagrangian model (so-calledLagrangian model), and (2) Eulerian-Eulerian model (Eulerianmodel). In the Lagrangian model the explicit motion of theinterface is not modeled. Thus, fluid motions around individualparticles are not captured. The continuous phase (gas phase) iscalculated using an Eulerian framework and the trajectories ofparticles are treated in a Lagrangian framework. The interfacebetween gas and solid phases is calculated by an average valueof the area bounded by a number of particle trajectories. Hence,a large number of particle trajectories should be used to obtainmeaningful hydrodynamic properties of the continuous phase(Vejahati et al., 2009). The Lagrangian model is normally limitedto a relatively small number of particles because of computationalexpense (Taghipour et al., 2005).

The second approach, Eulerian model, is considered as themost common approach for fluidized bed simulations (Pain,Mansoorzadeh, & de Oliveira, 2001). Both solid and gas phases arecalculated in an Eulerian approach based on the interpenetratingcontinuum assumption. In this approach, the trajectories of parti-cles are obtained at a hypothetical level rather than at a physicallevel in comparison with the Lagrangian model. The Eulerian modelmakes it possible to be applied to multiphase flow processes con-taining a large volume fraction of solid particles (Benyahia et al.,2000; Huilin et al., 2003a; Mathiesen, Solberg, & Hjertager, 2000).

In order to represent the particulate phase using the Eulerianmodel, additional closure laws are required to describe the rheol-ogy of the fluidized particles. An extension of the classical kinetictheory of gases to the dense particle flow is most commonly used.This approach provides explicit closures that take into accountthe energy dissipation resulting from particle–particle collisions bymeans of the restitution coefficient (Goldschmidt, Kuipers, & vanSwaaij, 2001; Huilin et al., 2003a; Reuge et al., 2008). The resti-tution coefficient quantifies the elasticity of the particle collisionsand ranges from 0 for inelasticity to 1 for fully elasticity (Taghipouret al., 2005). However, values of 0.9–0.975 are commonly used forthe gas–solid flows in turbulent risers and circulating fluidized bed(CFB) systems (Jiradilok, Gidaspow, Damronglerd, Koves, & Mostofi,2006; Jiradilok, Gidaspow, & Breault, 2007; Jiradilok et al., 2008;Zhang, Lu, Wang, & Li, 2008).

Limited studies have been reported on CFD simulation investi-gating both the riser and gasifier. In this work, a two dimensional(2D) CFD simulation is carried out to study hydrodynamics of acold-mode DFB gasifier including the riser and gasifier using acommercial CFD code (Fluent Inc., USA). Experiments were alsoconducted on a pilot-scale DFB in the cold mode. The solid cir-culation rate and solid holdup obtained from CFD simulation arecompared with those measured by experiment. In addition, hydro-dynamics of the hot mode is predicted at a given temperatureprofile along the riser and gasifier measured by experiment. Toour knowledge, it is the first time to demonstrate the similarityof hydrodynamics between the cold and hot modes by the CFDsimulation.

2. Experiment

Experiments for the cold-rig were carried out in a dual flu-idized bed reactor made of Plexiglas as shown in Fig. 1. The systemconsists of a riser (0.04 m width × 0.11 m depth × 4.5 m height), acyclone with downcomer, a BFB gasifier (0.285 m width × 0.11 m

depth × 2.13 m height) and a loop-seal (0.178 m width × 0.11 mdepth × 0.41 m height) which connects the BFB gasifier and riser.The positions of vertical aeration, supply chamber aeration, andrecycle chamber aeration are shown in the loop-seal in Fig. 2. These

50 T.D.B. Nguyen et al. / Computers and Chemical Engineering 36 (2012) 48– 56

Fig. 1. Schematic drawing of the cold-mode dual fluidized bed (1, riser; 2, cyclone;3, ball valve; 4, downcomer; 5, BFB gasifier; 6, loop-seal; 7, air box).

Table 1Physical properties of silica sand particles.

Description Values

Mean diameter (�m) 250Particle density (kg/m3) 2466

atsTma(ua

tion of mass, momentum and energy. The Eulerian model with the

Bulk density (kg/m3) 1281

ir injections make a better circulation of the particles from the risero BFB gasifier. Silica sand particles were used as a bed material. Theystem was operated at the ambient condition (25 ◦C and 1 atm).he physical properties of the bed material are given in Table 1. Theinimum fluidization velocity (Umf = 0.0603 m/s) was measured

s a function of gas velocity in the gasifier. The terminal velocity

Ut = 1.403 m/s) was calculated from (Haider & Levenspiel, 1989)sing the measured solid density, particle diameter (see Table 1)nd estimated sphericity of the sand particles.

Fig. 2. Schematic drawing of the loop-seal.

To understand effects of the gas velocity in the riser (Ug,r) andthe recycle chamber aeration velocity (Ug,rc) on the solid circula-tion of bed material (Gs), six experimental runs were conductedwith the operating conditions indicated in Table 2. The solid inven-tory (Iv) of 35 kg was initially loaded to the BFB gasifier for allexperimental runs. The gas velocity of the gasifier (Ug,b), verticalaeration velocity (Ug,vertical), and supply chamber aeration velocity(Ug,sc) were fixed. The recycle chamber aeration velocity (Ug,rc) var-ied from 0.0 to 0.18 m/s (=3Umf) for Runs 1–4 where Ug,r was setat 3.5 m/s. In Runs 5 and 6, the gas velocity of the riser (Ug,r) wasfixed at 4.0 m/s, while recycle chamber aeration velocities were 0.0and 0.06 m/s (=Umf), respectively. Several vertical aeration posi-tions were located along the downcomer of the loop-seal. In thisstudy, only one injection point was used with the height to baseline (h/l) of 2.5, where the height to base line (h/l) is defined as theratio of the height (h) from the bottom of the loop-seal to the widthof the loop-seal downcomer (l = 0.04 m).

After the system had reached a steady-state, the ball valve (posi-tion no. 3 in Fig. 1) in the downcomer was closed to measure thesolid circulation rate (Gs). The ascending time of the particles to theknown distance was measured in the transparent downcomer. Gs

was then determined by the accumulated particle mass divided bythe cross-sectional area and the ascending time (Goo et al., 2008).

Pressure taps connected to pressure transducers (DPLH series,Sensys Korea) were mounted to measure absolute and differentialpressures along the riser. When the system had reached a steadystate, the pressure drop (�P) of the riser was measured by thetransducers and recorded in the data acquisition system. The solidholdup also known as the average of the solid volume fraction (˛s)at each height was determined by the following linear relationshipbetween the time averaged pressure drop gradient (�P/�L) andthe solid holdup (Arena, Cammarota, & Pistone, 1986):

(�P/�L)g

= ˛s�s + (1 − ˛s)�g ∼= ˛s�s (1)

All the symbols used here are described in the nomenclature.

3. CFD model and simulation

The governing equations of the system include the conserva-

multiphase k-ε turbulence model which consists of a set of momen-tum and continuity equations for the gas and solid phase is usedin this study. The properties of the solid phase are obtained by

T.D.B. Nguyen et al. / Computers and Chemical Engineering 36 (2012) 48– 56 51

Table 2Operating conditions of the six experimental runs.

Description Run 1 Run 2 Run 3 Run 4 Run 5 Run 6

Solid inventory, Iv (kg) 35 35 35 35 35 35Gas velocity of the gasifier, Ug,b (m/s) 0.12 0.12 0.12 0.12 0.12 0.12Gas velocity of the riser, Ug,r (m/s) 3.5 3.5 3.5 3.5 4.0 4.0Vertical aeration velocity, Ug,vertical (m/s) 0.06 0.06 0.06 0.06 0.06 0.06

0.06 0.06 0.06 0.06 0.060.06 0.12 0.18 0.00 0.062.50 2.50 2.50 2.50 2.50

aZ

3

w

a

wg

et

w

ewV

asfeSVsUp

Supply chamber aeration velocity, Ug,sc (m/s) 0.06

Recycle chamber aeration velocity, Ug,rc (m/s) 0.00

Height to base line, h/l 2.50

pplying the kinetic theory of granular flows (Taghipour et al., 2005;immermann & Taghipour, 2005).

.1. Governing equations

Mass conservation equations of the gas (g) and solid (s) phasesithout mass transfer between the phases may be expressed as:

∂

∂t(˛g�g) + ∇(˛g�g�vg) = 0 (2)

∂

∂t(˛s�s) + ∇(˛s�s�vs) = 0 (3)

Momentum conservation equations of the gas and solid phasesre given by:

∂

∂t(˛g�g�vg) + ∇(˛g�g�v2

g) = −˛g∇p + ∇�g + ˛g�g�g + Kgs(�vg − �vs)

(4)

∂

∂t(˛s�s�vs) + ∇(˛s�s�v2

s ) = −˛s∇p − ∇ps + ∇�s + ˛s�s�g

+ Kgs(�vg − �vs) (5)

here �g is the gravity. �g and �s are the viscous stress tensors ofas and solid, respectively.

The conversion of the kinetic energy of moving particles isxpressed by the granular temperature (�s), which is derived fromhe kinetic theory of granular flow:

32

[∂

∂t(�s˛s�s) + ∇(�s˛s�vs�s)

]= (−psI + �s) : ∇�vs + ∇(k�s∇�s)

− ��s + gs (6)

here gs is the fluctuation energy exchange between gas and solid.Constitutive equations are required to close the governing

quations. These constitutive relations are used when dealingith hydrodynamics of multiphase flows (Taghipour et al., 2005;ejahati et al., 2009; Zimmermann & Taghipour, 2005).

In Eqs. (4) and (5), the momentum exchange between the solidnd gas phases was determined by the drag force which is repre-ented by an interphase exchange coefficient (Kgs). Several modelsor the gas–solid interphase coefficients were reported in the lit-rature when dealing with multiphase flow such as Gidaspow,yamlal-O’Brien, and Wen-Yu drag laws (Taghipour et al., 2005;ejahati et al., 2009; Zimmermann & Taghipour, 2005). In thistudy, the Gidaspow drag function available in Fluent (Fluent Inc.,SA) was used to calculate the momentum exchange between sandarticles and gas phase in the DFB system:

∣ ˛2s �g ˛s�s ∣ ∣

Kgs∣Ergun= 150

˛gd2s

+ 1.75ds

∣�vs − �vg∣ , ˛g < 0.8 (7)

Kgs∣∣Wen-Yu

= 34

CD˛s˛g�g

ds

∣∣�vs − �vg∣∣˛−2.65

g , ˛g ≥ 0.8 (8)

Fig. 3. 2D computational geometry of the dual fluidized bed.

where CD = (24/˛gRes)[1 + 0.15(˛gRes)0.678] and Res =�sds

∣∣�vs − �vg∣∣/�g. The Gidaspow model is a combination of the

Ergun equation and the Wen and Yu model (Huilin & Gidaspow,2003). Since there is a step change in Kgs at ˛g = 0.8 which maylead to an numerical instability, the following smoothing functionis applied (Huilin & Gidaspow, 2003):

Kgs = ϕKgs∣∣+(1 − ϕ)Kgs

∣∣Wen-Yu

(9)

in which ϕ is the weighting function:

ϕ = arctan(

150 × 1.75(0.2 − ˛s)�

)+ 0.5 (10)

Details of other drag functions and constitutive equations arefound elsewhere (Almuttahar & Taghipour, 2008a; Zhang et al.,2008).

3.2. Simulation setup

The governing equations are solved using the finite volumeapproach in Fluent (Fluent Inc., USA). The 2D computational domainof the pilot-scale DFB gasifier is constructed as shown in Fig. 3.The spiral flow in the cyclone is neglected because of the 2D

52 T.D.B. Nguyen et al. / Computers and Chemical Engineering 36 (2012) 48– 56

Fig. 4. Distribution of solid particles after 5 initial sec

Table 3Simulation settings of the solid phase properties.

Parameters Setting value

Particle diameter, dp (m) 2.5 × 10−4

Restitution coefficient, εss 0.9

sa2flr&corbwi

(iflwsaTv

ptsamb2t

Initial solid packing, ˛s,initial 0.519Packing limit, ˛s,max 0.63

implification and the residence time of the particles in the cyclonend the downcomer is shortened. However, it is expected that theD model is capable of predicting the main features of the gas–solidow in the DFB gasifier since the riser is operated in fast fluidizationegime at a relatively low solid flux (Gs < 100 kg/m2/s) (Almuttahar

Taghipour, 2008b). The domain is discretized by about 62,000ells having the maximum mesh interval spacing of 0.005 m. Mostf them are rectangular except the connecting channel between theiser and the cyclone. The analysis of grid size sensitivity reportedy Vejahati et al. (2009) showed that the mesh spacing of 0.005 mas adequate for satisfactory prediction of hydrodynamics in flu-

dized beds.Unsteady-state CFD simulation of each run mentioned above

see Table 2) was performed for 30 s of the real time. To avoidnstability and poor convergence in simulation of the multiphaseows, a small time step size of 0.001 s with 100 iterations/time-stepere used until the relative convergence criterion of 1 × 10−3 was

atisfied. The Phase-Coupled SIMPLE (PC-SIMPLE) algorithm waspplied for the pressure–velocity coupling (Vejahati et al., 2009).he gas phase was set with the density of 1.225 kg/m3 and theiscosity of 1.7894 × 10−5 kg/m s.

The settings of the solid phase are listed in Table 3. The meanarticle diameter of particles was given at 2.5 × 10−4 m. The resti-ution coefficient (εss) of 0.9–0.99 was reported for glass beads andilica sand particles with the average diameter of 300 �m (Pain etl., 2001; Taghipour et al., 2005). The coefficient of 0.9 was com-

only used in many researches related to the gas–solid fluidized

ed systems (Almuttahar & Taghipour, 2008a; Jiradilok et al., 2007,008; Reuge et al., 2008; Zimmermann & Taghipour, 2005). Thus,he restitution coefficient was set to 0.9 in this study. The initial

onds for Run 1 (Ug,r = 3.5 m/s and Ug,rc = 0 m/s).

solid packing (˛s,initial = 0.519) is the initial solid volume fractionof the bed material which was calculated from the air density, theparticle density, and bulk densities of the silica sand. The packinglimit (˛s,max) specifies the maximum volume fraction of the parti-cles. For mono-dispersed spherical particles as used in the presentwork, the packing limit is 0.63 (Fluent, 2007).

4. Results and discussion

Simulation results of the six runs given in Table 2 were obtainedafter 30 s of the real time. These results are presented both visuallyand quantitatively to examine the hydrodynamics of the gas-solidflow in the pilot-scale DFB. The hydrodynamic behaviors of thesolid–gas flow at room temperature and at high temperature werecompared on the basis of CFD simulation results.

4.1. Start-up flow pattern

At the beginning of the experiments, the silica sand was loadedin the BFB gasifier section, which is shown in Fig. 4a for Run 1. Airwas then introduced to the gasifier, the loop-seal and the riser withthe superficial velocities given in Table 2. Consequently, the bedmaterial in the gasifier was impulsively fluidized and transportedto the riser through the loop-seal. Initially, the bed height of the BFBleveled off, since a certain part of the bed material was transportedto the riser (see Fig. 4b).

Gas bubbles were then formed along the bed of the gasifier andthe system gradually reached a stable state. The chaotic transientgeneration of bubbles formed within the axisymmetric distribu-tion of the solid particles (see Fig. 4b–d) is observed in the BFB asreported in the literature (Taghipour et al., 2005). The system isfully developed after 5 s as seen in Fig. 4.

The simulation results show well that in the BFB gasifier smallbubbles at the bottom of the bed become larger, as they move

upwards due to their coalescence (see Fig. 4b–f). These bubblesare stretched because of the bed wall effects and interactions withother bubbles. The hydrodynamic behaviors were also reported inBehjat et al. (2008) and Zimmermann and Taghipour (2005).

T.D.B. Nguyen et al. / Computers and Chem

10.00

20.00

30.00

40.00

50.00

0.200.150.100.050.00

Recycle chamber aeration velocity, Ug,rc (m/s)

Solid

circ

ulat

ion

rate

, Gs

(kg/

m2 s)

Exp. - Ug,r = 3.5 m/sSim. - Ug,r = 3.5 m/sExp. - Ug,r = 4.0 m/sSim. - Ug,r = 4.0 m/s

Ft

4

phmctsatH

egtttvb

s4E2gmTtriiair

sm

4

ggt

ti

ig. 5. Effect of the recycle chamber aeration velocity (Ug,rc) and the gas velocity tohe riser (Ug,r) on the solid circulation rate (Gs).

.2. Solid circulation rate (Gs)

In the DFB gasifier, the solid circulation of the hot bed-materialslays a critical role, since the heat carried by the solid materialeated from the combustor is supplied to the gasification endother-ic reactions. For the given system, an increase in the solid

irculation rate will reduce difference of temperatures betweenhe gasification and combustion zones. On the other hand, a higherolid flux between the riser and gasifier can convey more unre-cted char from the gasification to combustion zone which reduceshe required amount of additional fuel (Kaiser, Löffler, Bosch, &ofbauer, 2003).

The solid circulation rate is affected by several operating param-ters such as gas velocities to the loop-seal, the riser, and theasifier. However, it is controlled mainly by the gas velocities tohe loop-seal and riser (Goo et al., 2008; Namkung et al., 1999). Inhis work, the effects of the gas velocities into the riser (Ug,r) ando the recycle chamber of the loop-seal (recycle chamber aerationelocity, Ug,rc) on the solid circulation rate (Gs) were determinedy experiment and CFD simulation.

Both simulation results and experimental measurements of theolid circulation rate (Gs) are shown in Fig. 5 at Ug,r = 3.5 m/s and.0 m/s as a function of the recycle chamber aeration velocity (Ug,rc).xperimental data of Ug,r = 3.5 m/s showed that Gs increased from4 to 41 kg/m2 s, when Ug,rc ranging from 0.0 to 0.18 m/s (3Umf). Theas introduced into the recycle chamber of the loop-seal providesomentum to the upward transportation of the solid particles.

hus, an increase in Ug,rc leads to the increase of the solid flux acrosshe loop-seal and in turn leads to an increase in the solid circulationate. The hydrodynamic behavior was also confirmed in an exper-mental study reported by (Goo et al., 2008). At Ug,r = 4.0 m/s, thencreasing rate of Gs with respect to Ug,rc is higher than that of Gs

t Ug,r = 3.5 m/s (see Fig. 5), since a larger amount of solid particlesn the recycle chamber are entrained by the upward flow along theiser at a higher flux.

The simulation results of the circulation rate obtained from theix runs agree well with experimental data (see Fig. 5). The maxi-um error of about 10% is found in Run 4.

.3. Axial solid holdup distribution

A constant rate of the solid circulation between the riser and BFBasifier should be maintained for the stable operation of the DFBasification system, as mentioned above. The solid holdup along

he riser is related to the stability of the solid circulation.

The axial solid holdup distribution along the riser obtained fromhe simulation results of Runs 1, 4, and 5 was presented in compar-son with experimental data in Fig. 6. It is observed that the solid

ical Engineering 36 (2012) 48– 56 53

fraction is high at the lower part and is low at the upper part, dueto the particle accumulation in the lower part of the riser duringthe transportation from the loop-seal, which was also reported inthe literatures (Goo et al., 2008; Jiradilok et al., 2008; Zhang et al.,2008).

The axial solid holdup along the riser at the given gas velocities inthe riser and gasifier increases with increasing the solid circulationrate, as seen in Fig. 6a–b. Since the gas flow is insufficient to entrainall the solids entering into the riser at a high solid circulation rate,the solid particles begin to accumulate at the lower part of the riserto form a dense phase. The higher the solid circulation rate thelarger the accumulation amount of the particles at the lower partof the riser. This results in an increase in the axial solid holdup alongthe riser, as the solid circulation rate increases.

The CFD model predicts reasonably the axial solid holdupdistribution for the three runs (Runs 1, 4, and 5) except some dis-crepancies happened for Run 1. As shown in Fig. 6a, a significantdeviation between measurement and computation is observed atthe upper part of riser. The over prediction for Run 1 may be resultedfrom the two dimensional (2D) simplification. This limitation ofthe 2D model was also reported in the literature (Jiradilok et al.,2008; Peirano, Delloume, & Leckner, 2001; Xie, Battaglia, & Pannala,2008; Xie, Battaglia, & Pannala, 2008). Xie et al. (2008a,b) statedthat a 2D system could be used successfully to simulate a bubblingregime rather than other fluidization regimes with low computa-tional resource. The values of additional terms appearing in the 3Dmodel increase for slugging and fast fluidization regimes as the gasinlet velocity increases, which is ignored in the 2D model (Xie et al.,2008b). On the other hand, Jiradilok et al. (2008) reported that thedeviation between measurement and simulation at the top of theriser was attributed to the down flow of particles not captured bythe 2D simulation. In this study, both the fast and bubbling fluidiza-tion regimes occurred in the riser and gasifier, respectively. Hence,a 3D CFD study would be useful to enhance the prediction accuracyof the solid holdup in the fast fluidization regime of the riser.

4.4. Comparison of CFD simulation results between the cold andhot modes

CFD simulation of the pilot-scale DFB system was conductedfor both the cold and hot modes to examine differences in hydro-dynamics. The boundary condition settings were based on theexperimental operating conditions given in Table 4 and on themeasured temperature profile.

The hot-rig experiment was conducted on the system havingthe same design as the DFB system used for the cold-rig. The entiresystem with the heat carrier materials (silica sand) was heated upto 600 ◦C prior to fuel (coal) loading by the electrical heater. Airwas introduced to the riser at 300 ◦C after preheating, while steamwas injected to the gasifier at 150 ◦C. The aeration in the loop-sealwas provided by air at room temperature (25 ◦C). The tempera-ture distribution along the riser, the gasifier, and the loop-seal wasmeasured, when the system reached a steady state. Here, the gasi-fication temperature was 800 ◦C in the BFB gasifier.

Two CFD simulations of one for the cold-rig and one for thehot-rig with the boundary conditions given in Table 4 were per-formed. With the purpose of hydrodynamic study, air was used asthe fluidizing agent in the BFB gasifier instead of steam and chem-ical reactions were not considered. The velocities of the inlet airflows introduced to the riser, gasifier, and loop-seal used in thesimulations were set as same as those of experimental conditions(see Table 4). However, in the cold-mode simulation, the temper-

atures of air introduced to the system were set at 25 ◦C, while inthe hot-mode simulation the temperatures of the inlet air to theriser, gasifier, and loop-seal were set to be 100, 300, and 150 ◦C,respectively which were the same as the temperatures of the gas

54 T.D.B. Nguyen et al. / Computers and Chemical Engineering 36 (2012) 48– 56

Table 4Hot-bed experimental operating conditions and boundary conditions of the cold- and hot-rig simulations.

Operating conditions Hot-bed Exp. Cold-rig Sim. Hot-rig Sim.

Solid inventory, Iv (kg) 35 35 35Gas velocity to the gasifier, Ug,b (m/s) 0.22 at 150 ◦Ca 0.22 at 25 ◦C 0.22 at 150 ◦CGas velocity to the riser, Ug,r (m/s) 5.0 at 300 ◦C 5.0 at 25 ◦C 5.0 at 300 ◦CVertical aeration velocity, Ug,vertical (m/s) 0.06 at 25 ◦C 0.06 at 25 ◦C 0.06 at 25 ◦CSupply chamber aeration velocity, Ug,sc (m/s) 0.06 at 25 ◦C 0.06 at 25 ◦C 0.06 at 25 ◦CRecycle chamber aeration velocity, Ug,rc (m/s) 0.18 at 25 ◦C 0.18 at 25 ◦C 0.18 at 25 ◦CHeight/base line, h/l 2.50 2.50 2.50

flttpw

eTtgH(roee

oaOt

fatT

a Steam was used as feed gas.

ows used in the experiment. Moreover, in the hot-mode simula-ion the temperature of the initial sand was set to be the combustionemperature (as measured, T = 870 ◦C) and the wall boundary tem-eratures were tuned until the cross-sectional mean temperaturesere fit to the temperatures measured in the hot-bed experiment.

The temperature distributions along the riser obtained from thexperiment and simulation results of the hot bed are shown in Fig. 7.he temperature tends to decrease gradually from the bottom tohe top of the riser, because of the heat loss and the endothermicasification reactions of the certain amount of char with CO2 and2O in the flue gas. The temperature at the bottom part of the riser

870 ◦C) was higher than that at the gasifier (800 ◦C) due to the heateleased from the combustion of the unreacted char in the presencef the air. The temperature profile along the riser was relatively wellstimated for the hot-mode CFD simulation compared to that of thexperiment.

The two simulations have the same result at a circulation ratef 41.2 kg/m2 s. The solid holdup along the riser section for the coldnd hot rigs obtained from the CFD simulation is presented in Fig. 8.nly a small difference is observed from the solid holdup between

he two simulations at the lower part of the riser.Fig. 9 depicts the horizontal distributions of the solid volume

raction and the velocity of the particles at riser heights (H) of 1.0

nd 3.0 m for the cold and hot mode simulations. These distribu-ions were taken from the time-averaged values from 20 s to 25 s.hey are not symmetric because the loop-seal is connected to the

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.30.20.10

Solid holdup (-)

Ris

er h

eigh

t (m

)

Exp. - Run 1Sim. - Run 1

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.10

Solid

Ris

er h

eigh

t (m

)

(a) (b)

Ug,r = 3.5 m/s Ug,rc = 0. 0 m/s

Ug,Ug,

Fig. 6. Axial solid holdup distribution along the riser of the

right side of the riser. The horizontal variation of both the solidvolume fraction and the solid velocity is bigger at H = 1 m than atH = 3 m because of the loop-seal situated at the bottom of the riser.At H = 3 m, the two profiles are evenly distributed along the hori-zontal direction. At H = 1 m, the solid volume fraction and the solidvelocity are bigger in the left side than in the right side of the riser.There exists some discrepancy between the cold and hot modes inthe two distributions, but they have a similar trend.

Eqs. (2) and (3) for the mass balances of gas and solid,respectively, are not temperature-dependent. Energy dissipation ofparticles in Eq. (6) is affected little by temperature because the soliddensity (�s) and velocity (vs) are almost the same in the two simu-lations. However, the momentum exchange between gas and solidin Eqs. (4) and (5) is related to the interphase exchange coefficient(Kgs) which is expressed in Eq. (7). Since Kgs is proportional to thegas density (�g) and viscosity (�g) which decrease with the increaseof temperature, Kgs and the pressure drop (�P) then decrease, whentemperature increases.

Due to the temperature dependence of Kgs mentioned above, thesolid holdup (˛s) of the hot rig is less than that of the cold one at thelower part of the riser. However, the difference of ˛s between tworigs is small at the upper part because of the small solid fraction(see Fig. 8). Therefore, it is confirmed that the hydrodynamics of

the cold mode gives a meaningful knowledge prior to the hot modeoperation, which was also reported in an experimental research of(Xu, Murakami, Suda, Matsuzawa, & Tani, 2006).

0.30.2

holdup (-)

Exp. - Run 4Sim. - Run 4

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.30.20.10

Solid holdup (-)

Ris

er h

eigh

t (m

)

Exp. - Run 5Sim. - Run 5

(c)

r = 3.5 m/s rc = 0.18 m/s

Ug,r = 4.0 m/s Ug,rc = 0.0 m/s

cold-mode DFB. (a) Run 1, (b) Run 4, and (c) Run 5.

T.D.B. Nguyen et al. / Computers and Chemical Engineering 36 (2012) 48– 56 55

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

1000950900850800

Temperature (oC)

Ris

er h

eigh

t (m

)Experiment

Simulation

Fig. 7. Comparison of hot-mode experimental temperature distribution along theriser with that obtained from CFD simulation.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.30.20.10

Solid holdup (-)R

iser

hei

ght (

m)

Sim. - Hot bedSim. - Cold bed

Fig. 8. Solid holdup distributions along the riser obtained from the CFD simulationin the cold and hot mode operations.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.040.0350.030.0250.020.0150.010.0050

Riser horizontal position (m)

Solid

vol

ume

frac

tion

(-)

Cold bed - H = 1.0 mCold bed - H = 3.0 mHot bed - H = 1.0 mHot bed - H = 3.0 m

00.5

11.5

22.5

33.5

4

4.55

0.040.0350.030.0250.020.0150.010.0050

Riser horizontal position (m)

Sand

vel

ocity

(m/s

)

Cold bed - H = 1.0 mCold bed - H = 3.0 mHot bed - H = 1.0 mHot bed - H = 3.0 m

(a)

(b)

Fig. 9. Horizontal distributions of (a) solid volume fraction and (b) sand velocity at the riser heights of H = 1.0 and H = 3.0 m for the cold and hot mode operations.

5 d Chem

5

caflBitpd

ftctgmtd

A

RE

R

A

A

A

B

B

C

FF

G

G

H

H

6 T.D.B. Nguyen et al. / Computers an

. Conclusions

A pilot-scale dual fluidized bed (DFB) was constructed in theold-rig to investigate hydrodynamics of the system consisting of

riser as a combustor, a cyclone with downcommer, a bubblinguidized bed (BFB) for gasification, and a loop-seal connecting theFB and the riser. Its hydrodynamic characteristics were examined

n the cold mode by both computation and experiment. The mul-iphase Eulerian model incorporating the kinetic theory of solidarticles was applied for computational fluid dynamics (CFD). Sixifferent experimental runs were conducted in the cold-rig DFB.

The CFD simulation results predict well the solid circulation rateor all the six experimental sets. Some discrepancies are found forhe axial solid holdup distribution along the riser, which may beaused by the limitation of the 2D simulation in the fast fluidiza-ion regime. When the temperature distribution along the riser andasifier is given by the experimentally-measured values for the hot-ode CFD simulation, a hydrodynamic similarity is observed with

he CFD simulation of the cold mode, which is computationallyemonstrated at the first time in the DFB system.

cknowledgement

This work was supported by Energy Efficiency and Resources&D program (2009T100100675) under the Ministry of Knowledgeconomy, Republic of Korea, and SK energy Co., Ltd.

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