Computational Fluid Dynamic Simulation Based Cluster Structures

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Computational Fluid Dynamic Simulation Based Cluster Structures-Dependent Drag Coefficient Model in Dual Circulating Fluidized Beds of Chemical Looping Combustion Wang Shuai, Yang Yunchao, Lu Huilin,* Xu Pengfei, and Sun Liyan School of Energy Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China ABSTRACT: A computational fluid dynamic (CFD) model for the dual circulating fluidized beds of chemical looping combustion technology has been developed. A continuum two-fluid model is used to describe both the gas and solid phases. Detailed submodels to account for fluidparticle and particleparticle interaction forces were incorporated. The gassolids drag coefficient is predicted by means of the cluster structures-dependent (CSD) drag coefficient model. Flow behavior of gas and particles in the air reactor (AR) and fuel reactor (FR) is predicted. The solid circulation rate increases with the increase of solids inventory of the AR and FR. When the loop seal is connected to dual circulating fluidized beds of AR and FR, the fluidizing state of AR and FR is found to be affected by hydrodynamics in the loop seals.

1. INTRODUCTION Chemical-looping combustion (CLC) is a method where a gaseous fuel, such as natural gas or syngas, can be burnt with inherent separation of the greenhouse gas CO2.1 In the CLC system, it requires many unit operations involving gassolid or granular flow. A CLC system generally consists of two reactors, a fuel reactor (FR) and an air reactor (AR). The fuel is oxidized in the FR by using granular metal oxides. The AR reoxidizes the reduced carrier. After exiting the AR the oxidized carrier is separated by an expansion region or a cyclone and returned to the FR. Thus the CLC reactor basically is a circulating fluidized bed (CFB) where the solid particles are circulated between the AR and FR. Since gassolids contact and solids transport between the AR and FR reactors is very important in CLC, the AR and FR are designed as fluidized bed reactors. Lyngfelt et al.2 have proposed a reactor system that consists of a circulating fluidized bed (AR) and a bubbling fluidized bed (FR). A very similar design is described by Ryu et al.,3 in which the FR is operated in the turbulent regime. Thus, the gassolids contact in the FR is increased and the possible bypass of fuel in the bubble phase is reduced. This dual fluidized bed reactor is widely used not only in the dual fluidized bed gasifier (DFBG)46 but also in the chemical looping combustion (CLC).7 Compared with other interconnected fluidized beds, in the dual circulating fluidized bed (DCFB) system shown in Figure 1, the AR is designed as a circulating fluidized bed determining the global solids circulation rate, and the FR is designed as a second circulating fluidized bed reactor with the return loop of the entrained solids into itself.810 The lower loop seal connecting the two reactors represents a continuation of the reactor bodies, and the upper loop seal and the internal loop seal close the global circulation loop. Therefore, the global solids circulation rate depends on the AR and FR fluidization. Risers can be easily adopted to operate in the specific conditions of the chemical looping arrangement. Hence the detailed computational fluid dynamic analyses of such systems would r 2011 American Chemical Society

Figure 1. DCFB reactor system designed as circulating fluidized beds.

allow and speed up the optimization of the process and scale-up. The modeling of flows of particles with computational fluid dynamics (CFD) has been progressed. Eulerian models consider all phases to be continuous and fully interpenetrating. The equations employed are a generalization of the NavierStokes equations for interacting continua. Owing to the continuum representation of the particulate phases, Eulerian models require additional closure laws to describe the rheology of the fluidized particles. In most recent continuum models, the constitutive equations according to the kinetic theory of granular flow (KTGF) are incorporated.11 This theory is basically an extension of the classical kinetic theory to dense particle flow, which Received: August 12, 2011 Accepted: December 20, 2011 Revised: December 20, 2011 Published: December 20, 2011 1396

dx.doi.org/10.1021/ie201797p | Ind. Eng. Chem. Res. 2012, 51, 1396–1412

Industrial & Engineering Chemistry Research provides explicit closures that take energy dissipation due to nonideal particleparticle collisions into account as a function of the local concentration and the fluctuating motion of particles owing to particleparticle collisions. Jung and Gamwo12 were the first to apply multiphase CFD modeling for chemical looping combustion processes using a multiphase hydrodynamic model MFIX code. Simulations of gassolid hydrodynamics and chemical reactions were performed by means of the commercial code FLUENT in the fuel reactor of a chemical looping combustion process.13 Simulations mentioned above restricted their considerations to the fuel reactor operated as a bubbling bed. Hydrodynamics of gas and particles in the chemical looping combustion process with the interconnection of a circulating fluidized bed and a bubbling fluidized bed is simulated by means of a modified K-FIX code.14 Distributions of concentration and velocity of particles are predicted in the air reactor and fuel reactor. Flow of clusters in the air reactor, bubbles in the fuel reactor, and pot-seal is observed. Mahalatkar et al.15 simulated the effect of superficial velocity and reactor temperature on the reduction reaction inside the fuel reactor by means of the commercial CFD code FLUENT version 6.3. The simulations are performed to study hydrodynamics of a dual-fluidized bed gasifier including the riser, a cyclone with downcommer, and bubbling fluidized bed using the commercial FLUENT CFD code.16 The solid circulation rate and concentration of particles are predicted from CFD simulations. A coupled model of both air and fuel reactors was developed using a multiphase fluid dynamics framework in an interconnected fluidized bed of chemical looping combustion system.17 The reduction in the air reactor as a high velocity riser and the oxidation in the fuel reactor as a bubbling fluidized bed are separately modeled by means of the commercial CFD software FLUENT version. The solid circulation rate and the solid flow characteristics in the loopseal were simulated in a dual circulating fluidized bed reactor by means of the CFD software Fluent without the consideration of the effect of frictional stresses.18 Although most fluidized beds are considered to operate mainly in the region of rapid granular flow, applications using the KTGF models without the incorporation of the frictional stresses often exhibit unphysical behavior such as the fountain problem described by Boemer et al.19 While the approach to transition from the kinetic theory of granular flow and the quasi-static theory was suggested by Savage et al.20 and successfully implemented in models.2123 They showed that the frictional stress as modeled considerably influences the bed dynamics. A critical comparison of the results obtained from the kinetic theory of the granular flow with the frictional stresses was studied both in the case of a uniformly bubbling fluidized bed and in a bed with a central jet.24,25 Simulations show the bubble shape and diameter are significantly sensitive to frictional stress in the fluidized bed. Since gassolids contact and solids transport between the reactors is very important in CLC, the AR and FR are designed as fluidized bed reactors. In the DCFB reactor system both the AR and the FR are operated in the fast fluidized bed regime.3 In this way, the gassolids contact in the AR and the FR is increased and the possible bypass of fuel in the bubble phase is reduced. Therefore, the FR can be optimized toward fuel conversion regardless of oxygen carrier circulation. Generally speaking, with chemical looping combustion in a DCFB unit, the concentration of particles is low in the riser, and flow of particles is dominated by particleparticle collisions. Particles are agglomerated and the clusters are formed. Constitutive

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models for the stresses of particles in the air reactor and fuel reactor can be deduced from the kinetic theory of granular flow, and the effect of clusters on gassolids drag force needs to be considered. On the other hand, the concentration of particles in the loop seals is high, and the particles are enduring frictional contact with multiple neighbors. The solid stresses in these zones are mainly due to frictional interactions between particles at points of sustained contact. The contributions from both collision and friction are comparable. Thus, it is of practical interest to synthesize a rheological model that combines the kinetic and frictional contributions. In present work, a gassolid two-phase flow model, involving a kinetic-frictional closure for the particle phase stresses, is proposed to simulate hydrodynamic behavior in a chemical looping combustion with two interconnected circulating fluidized beds. The kinetic stress of the solid phase is based on the kinetic theory of granular flow. For frictional stress, a normal frictional stress model proposed by Johnson and Jackson26 and a frictional shear viscosity model proposed by Schaeffer27 are used. The gassolids drag coefficient is predicted by means of the cluster structures-dependent (CSD) drag coefficient model.28 Detailed information on flow behavior in both AR and FR has been provided. It is expected that the present CFD model that has been validated with experiments can be applied to study CLC reactors.

2. GAS-PARTICLES TWO-PHASE FLOW MODEL IN CLC The hydrodynamic approach to gassolid two-phase flow systems is based on the principles of mass conservation and momentum balance for each phase. Conservation equations of mass and momentum of both phases result from the statistical average of instantaneous local transport equations.11 In this work, the governing equations are given below. 2.1. Governing Equations. For simplification, the following hypotheses are considered: (1) both phases are assumed to be isothermal, and no interface mass transfer and nonreaction are assumed; (2) both phases are continuous assuming a single gas phase and a single solid phase. The continuity equations for gas phase and solid phase are given in eq T1-1 and T1-2 in Table 1. Mass exchanges between the phases due to reaction are not considered. The momentum balance for the gas phase is given by the NavierStokes equation, modified to include an interphase momentum transfer term, and expressed by eq T1-3, where βgs is the interface momentum transfer coefficient, and τg the viscous stress tensor. The stress tensor of gas phase is expressed by eq T1-9, where μe is the viscosity of gas phase, and expressed by eq T1-10. The turbulent flow of gas phase is described by a standard k-ε turbulence model. Here k represents the turbulent kinetic energy and ε represents the dissipation rate of turbulent kinetic energy. Assuming the influence of the dispersed particles on the gas phase is neglected, the equations for turbulent kinetic energy and dissipation rate are given in eq T1-6 and T1-7. The constants involved in these equations are c1 = 1.44, c2 = 1.92, cμ = 0.09, σk = 1.0, and σε = 1.0. These values have been shown to resolve the flow field in fluidized beds by Almuttahar et al.29 and Hartge et al.,30 and have been used in the present work. Note that the standard k-ε model does not account for the interphase turbulence momentum transfer. It is questionable to use the turbulence model for modeling the gas turbulence in the gassolid two-phase flow directly since 1397

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Industrial & Engineering Chemistry Research

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Table 1. Mathematical Model of GasSolid Flow

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Table 1. Continued

Figure 2. Clusters and dispersed particles in a computational cell.

the model was originally developed for modeling fluids. Thus, an accurate modeling for gas turbulence in chemical looping combustion systems is necessary to get a more complete validation. The solids phase momentum balance is given by eq T1-4, where τs is the stress tensor of particles. There are two possible mechanisms inducing the fluctuations of particle velocity:

interparticle collisions and particle interactions with turbulent fluctuations in the gas phase. Interparticle collisions play a crucial role in sufficiently dense suspensions. Equivalent to the thermodynamic temperature for gases, the granular temperature can be introduced as a measure for the energy of the fluctuating velocity of the particles.11 The equation of conservation of solids fluctuating energy is expressed by eq T1-5. 1399



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Table 2. Correlations and Parameter Used in the Model

2.2. Kinetic and Frictional Stress Models. In the loop seal and the pipeleg (downcomer), the concentration of particles is high. The interaction between particles by friction dominates. Under such conditions, the normal reaction forces and the associated tangential frictional forces of sliding contacts are the major contribution to the particle stresses. At low particle concentrations, however, the stresses induce mainly from particleparticle collisions. The solids stress tensor, τs, is the sum of the kinetic stress tensor τs,k and the frictional stress tensor τs,f,3134 and each contribution evaluates as follows: ( τs, k εs e εs, min τs ¼ ð1Þ τs, k þ τs, f εs > εs, min

where εs,min is the solid concentration at the transition point when frictional stresses become important. From eq 1, it is assumed that the frictional and kinetic stresses are additive at εs>εs,min. Each contribution evaluates as if it acts alone. Equation 1 captures both the shear flow regime where the kinetic and collisional contributions dominate, and the quasi-static flow regime where the friction dominates. However, the step transitioning (discontinuity) from the shear flow regime to the quasi-static flow regime not only causes numerical instabilities leading to slow convergence but also generates spurious solutions in numerical simulations. In order to address these

problems, an approximate transitioning function j is constructed to provide a smooth transition between the two regimes in the particle concentration space. Thus, the shear viscosity of particles is expressed by eq T1-16. In this work, the equation of kinetic part of solid viscosity μs,k is given eq T117.11 The frictional viscosity μs,f proposed by Schaeffer27 is expressed by eq T1-18, where ψ is the angle of internal friction and I2D is the second invariant of the deviatoric part of the rate of strain tensor. The value of ψ is taken to be 28.5° for glass beads.33 The solid pressure is expressed by eq T1-12, where the kinetic portion of solids pressure ps,k is given eq T1-13. For the frictional pressure of particles, ps,f, the semiempirical model proposed by Johnson and Jackson26 is used and expressed by eq T1-14, where F, n, and p are empirical material constants. The values of empirical parameters of εs,min, F, n, and p are taken to be 0.5, 0.05, 2.0, and 5.0 for glass beads,33 respectively. These values have been shown to resolve the flow field in fluidized beds22,3537 and have been used in the present work. 2.3. Drag Coefficient Model. In the riser, the clusters of particles are formed. The particles are considered to be either in the particle-rich dense phase or in the gas-rich dilute phase. This means that in a grid cell, as shown in Figure 2, particle movements are in the form of clusters in the dense phase or in the form of dispersed particles in the dilute phase.38 The volume fractions of dense and dilute phases are defined by f = Vden/V and 1400



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Table 3. Model for Cluster Structure-Dependent Drag Coefficient

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1 f = Vdil/V, where V is the control volume of a grid cell, Vden and Vdil are the respective volumes of dense and dilute phases in a grid cell. The porosities of dense phase and dilute phase are εden = Vg,den/Vden and εdil = Vg,dil/Vdil, where Vg,den and Vg,dil are the gas volumes of dense and dilute phases in the control volume of a grid cell. To establish a mathematical model for both dense phase and dilute phase, we make the following assumptions: (1) The dense phase exists as spherical clusters. (2) Dispersed particles in the dilute phase are uniform. (3) Clusters in a control volume are homogeneously dispersed. Harris et al.39 presented correlations for predicting the size, shape, and density of particle clusters in the risers. The cluster size, shape, solid concentration, and velocity are in radial and axial variations. Thus, the formation of particle clusters affects flow behavior of particles and solids mixing. When the clusters are analyzed as large particles, the drag from the dilute phase will act on the clusters, that is, the dense phase. Both phases are combined through the drag term to form the third phase (mesoscale interface). Therefore, an inhomogeneous gassolid flow in a grid cell consists of three homogeneous flows. The related definitions and structure parameters are summarized in Table 2. The mean velocities of gas phase and solids phase in the cell are expressed by eq T2-1 and T2-2, where Ug,den and Ug,dil are the gas superficial velocities through the dense phase and dilute phase in the cell. Us,den and Us,dil are the superficial velocities of particles in the dense phase and dilute phase of the cell. The drag forces include the drag force components of dense phase Fden and dilute phase Fdil, and interfacial force between the dense and the dilute phases Fint. The expressions of drag force components Fden, Fdil, and Fint are given in Table 3. The momentum equation of gas phase in the dense phase and dilute phase of the cell at the steady state is28,38 ∂ ∂p ðf εden Fg ug, den ug, den Þ ¼ f εden nden Fden f εden Fg g ∂x i ∂xi ð2Þ ∂ ∂p ½ð1 f Þεdil Fg ug, dil ug, dil ¼ ð1 f Þεdil ndil Fdil ∂xi ∂xi nint Fint ð1 f Þεdil Fg g

ð3Þ

where u g,den and ug,dil are the gas velocity through the dense phase and the dilute phase and equal fU g,den/ε den and (1 f)U g,dil /(1 εden). From eqs 2 and 3, the relation of drag forces in the dense phase, the dilute phase, and the interfacial force between the dense and the dilute phases is ð1 f Þεdil nden Fden ¼ ndil Fdil þ nint Fint f εden þ ð1 f Þεdil Fg ðag, dil ag, den Þ

balance equation is at the steady state: ∂ ½ð1 f Þð1 εdil ÞFs us, dil us, dil ∂x i ¼ ð1 f Þð1 εdil Þ

∂p ∂xi

þ ndil Fdil ð1 f Þð1 εdil ÞFs g ∂ ½f ð1 εden ÞFs us, den us, den ∂x i ¼ f ð1 εden Þ

∂p þ nden Fden ∂xi

þ nint Fint f ð1 εden ÞFs g

where ag,dil = ∂(ug,dilug,dil)/∂xi and ag,den = ∂(ug,denug,den)/∂xi are the accelerations of gas in the dilute and dense phases. The solids momentum balance can be derived similarly to that of the gas in the dense phase and dilute phase. For flow of particles in the dilute phase and dense phase, the momentum

ð6Þ

From eq 5, an expression for the superficial slip velocity Udil of the dilute phase is derived and expressed by eq T3-13, where as,dil = ∂(us, dilus,dil)/∂xi is the acceleration of particles in the dilute phase. Thus, the superficial slip velocity Udil is solved at the specified ∂p∂xi which is obtained from numerical simulations in the computational cells. From eq 6, the expressions for the superficial slip velocity Uden of dense phase is also derived and expressed by eq T3-12, where as,den = ∂(us,denus,den)/∂xi is the accelerations of particles in the dense phase. We see that the superficial slip velocity Uden is computed at the specified εg and ∂p∂xi in which the porosity and gas pressure gradient are obtained from numerical simulations in the computational cells. Combining eqs 5, 6, and eq 4, the superficial slip velocities Uint of the interface are expressed by eq T3-14. Thus, the superficial slip velocity Uint depends upon εdil, εg, and ∂p∂xi which are determined from the numerical simulations of the computational cells. In eq T3-14, dc is the equivalent diameter of clusters. The cluster diameter is assumed to be inversely proportional to the energy used for suspension and transportation.40,41 Us εmf Us ds Umf þ g 1 εmax 1 εmf dc ¼ ð7Þ Fs εmf Us Umf þ g Ndf Fs Fg 1 εmf where εmax represents the maximum porosity beyond which clusters do not exist.42 The value of εmax was suggested to be 0.9997.4345 From the point of view of energy balance, the total energy input (characterized by the product of gas velocity and axial pressure gradient) is converted to the increase of kinetic energy via the acceleration, to the increase of potential energy via the vertical transport against gravity, and to the energy dissipations in the transport process via frictional loss. Thus, the energy consumed by drag force per unit mass of particles, Ndf, is 1 ½nden Fden Ug, den þ ndil Fdil Ug, dil N df ¼ ð1 εg ÞFs þ nint Fint Ug, dil ð1 f Þ

ð4Þ

ð5Þ

ð8Þ

The stability of gassolid flow system calls for mutual coordination, as much as possible, between the gas and particle phases to follow their respective tendencies. Characteristically, the particles tend to aggregate into clusters to reduce the gas flow resistance, while the gas phase tends to bypass the clusters instead of passing through them. Both the particles and the gas phases have their respective movement tendencies. That is, particles tend to array themselves with minimal energy loss by drag, while 1402



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Table 4. Reactor Geometry, Main Operating Parameters, and Modeling Parameters of AR and FR parameter

description

unit

AR

FR

H

reactor height

m

4.1

3.0

D ug

reactor diameter superficial gas velocity

m m/s

0.15 2.0

0.1593 2.0

d

particle diameter

μm

200

200

Fs

particle density

kg/m3

2600

2600

μg

gas viscosity

kg/(m s) 1.789 105 1.789 105

H0

static bed height

m

0.8

0.6

Dc

diameter of cyclone

m

0.15

0.15

Dd

diameter of downcomer m

0.05

0.05

Hd εs,o

height of downcomer m initial concentration of

0.5 0.5, 0.24

1.5 0.5, 0.24

0.9

0.9

Figure 3. Profile of concentration of particles predicted by different grids in the AR.

particles e

restitution coefficient of particles

ew

restitution coefficient of

0.9

0.9

0.5

0.5

particle-wall ϕ

specularity coefficient

the gas phase tends to choose an upward path with minimal resistance. From eq 8, it shows that the resistance includes the resistance between the gas phase and dispersed particles in the dilute phase, the resistance between the gas phase and clusters in the dense phase, and the interfacial interaction between the dilute phase and the dense phase. Therefore, the system is characterized by minimum energy loss by drag force per unit mass of the particles, Ndf, by which the particles aggregate into clusters and the gas flows with low resistance. Hence, the stability condition for the inhomogeneous gassolid system is needed to the extremum of energy consumed by drag force, for which the minimization of the energy dissipation by heterogeneous drag (MEDHD) is N df f minimum ¼ Ndf , min

ð9Þ

Hence, the equivalent diameter of clusters is calculated on the basis of eq 9. The drag force is represented by the term βgs(ug us), the product of the drag coefficient βgs and the slip velocity. In this manner, the relationship between structure parameters and cluster structuresdependent (CSD) drag coefficient can be written as follows βCSD ¼ ¼

εg Fgs Uslip εg 2 ½nden Fden þ ndil Fdil þ nint Fint jug us j

ð10Þ

Substituting eqs T3-9, T3-10 and T3-11 into 10, the CSD drag coefficient is expressed by " 2 3 εg Fg f ð1 εden ÞCden Uden 2 βCSD ¼ 4 jug us j ds # ð1 f Þð1 εdil ÞCdil Udil 2 f Cint Uint 2 þ þ εg g 0:8 ð11Þ ds dc

Us,dil. These structure parameters are determined under the specified operating conditions, and hence the drag coefficient βCSD can be predicted. For flow of particles with high concentrations, the correlations of drag coefficient proposed by Gidaspow11 are often used in the numerical simulations of fluidized beds. The drag coefficient is expressed by eq T3-2. To avoid discontinuity of these two correlations eq T3-1 and T3-2, a switch function jgs is introduced to give a smooth transition from the dilute regime to the dense regime. Thus, the drag coefficient becomes βgs ¼ ð1 jgs ÞβE þ jgs βCSD

ð12Þ

Note that in the CSD drag coefficient model the microscale description of the gas-particle interaction inside the dilute (εdil, Ug,dil and Us,dil) and dense (εden, Ug,den and Us,den) phases, the mesoscale description of cluster size (dc) and the operating conditions as macroscale parameters (gas velocity ug, solid velocity us, and gas pressure gradient ∂p/∂xi) are integrated together through the stability condition (MEDHD) establishing a multiscale drag coefficient model. Thus, the CSD drag coefficient model is linked together by the communications of the structure parameters of dispersed particles in the dilute phase and clusters in the dense phase, and gives a reasonable description of the mesoscale structure in gassolid flow. Hence, it bridges the particle-scale description and the macroscale parameters. 2.4. Boundary Conditions. The governing equations mentioned above are numerically solved with appropriate boundary and initial conditions. Initially, there are no motions for both the gas phase and the particles in the DCFB reactor system. The velocities of gas and particles are zero. Particles are filled in the riser, loop seals, cyclone, and pipeleg at the solids concentration of 0.5. The initial static bed heights in the AR and FR are constant. At the inlet, all velocities and volume fractions of gas phase and particles are specified in the AR and FR. The outlets of the cyclone of the AR and FR are modeled using a continuity condition for all variables, except for gas pressure. The gas pressure is set to be 1 atm. At the wall, the tangential and normal velocities of gas phase are set to zero (no slip condition). The normal velocity of the particles is also set at zero. The following boundary equations apply for the tangential velocity and granular temperature of particles at the wall:46 6μs εs, max ∂us, w pffiffiffiffiffi ut, w ¼ πjFs εs go 3θ ∂n

It can be observed that βCSD is as an implicit function of eight structure parameters of f, εdil, εden, dc, Ug,den, Ug,dil, Us,den and 1403

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Figure 4. Instantaneous concentration of particles in the air reactor and fuel reactor.

Figure 5. Instantaneous solid fluxes at the exits of AR and FR.

Figure 7. Profile of axial velocity of particles in the AR and FR.

Figure 6. Profile of concentration of particles in the AR and FR.

Figure 8. Profile of simulated pressure of the system.

ks θ ∂θw þ θw ¼ γw ∂n

pffiffiffi 3πjFs εs us 2 go θ3=2 6εs, max γw

ð14Þ

where

pffiffiffi 3πð1 ew 2 ÞFs εs go θ3=2 γw ¼ 4εs, max

ð15Þ

The simulations are carried out with a CLCCFD code which is based on K-FIX program previously used to model gassolid flow in circulating fluidized beds.47 This software allows free

implementation of extra equations, boundary conditions, and differencing schemes. The granular kinetic theory and the granular equations described in the previous section are implemented into this code. The conservative equations are discretized in finite differences equations that are solved using a pointrelaxation technique. The finite-difference equations are solved in a 2D computational mesh that can be uniform or nonuniform. The scalar variables are set at the center of the cells while the vector variables are placed at the boundaries of the cells. For convergence, the gas pressure is corrected in each cell at a time 1404



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Figure 9. Profile of solid mass flux at three positions of the system. Figure 11. Distribution of granular temperature in loop seals.

Figure 10. Profile of granular temperature of particles in the AR and FR.

until convergence is attained. The computations proceed until the entire computational domain is covered. In all simulations, a constant time step of 1.0 105 s is used. Time-averaged distributions of flow variables are computed covering a period of 20 s corresponding to 23 weeks of computational time on a PC (20GB hard disk, 128Mb RAM, and of 600 MHz CPU).

3. RESULTS AND DISCUSSION 3.1. Reference case. To be able to discuss the behavior of the DCFB reactor system, a reference case is defined. From this reference case, parameter variations are performed. Table 4 summarizes the main geometry and operating parameters of AR and FR. Even though identical solids distribution is defined in both reactors, the pressure drops are different in the AR and FR. Figure 1 shows the principal layout of an atmospheric DCFB reactor system. The air reactor has an inner diameter of 0.15 m and a height of 4.1 m. The fuel reactor is 0.159 m ID and 3.0 m in height. The lower loop seal between the fuel reactor and the air reactor is used to prevent gas mixing between the two reactors. Fluidizing air is injected into the lower loop seal (ug,lls), internal loop seal and upper loop seal (ug,ils and ug,uls). The inlet gas velocity ug,lls of the lower loop seal is 0.2 m/s. Both ug,ils and ug,uls are 0.05 m/s. The vertical distance from the bottom of upper loopseal to the inlet of FR is 1.2 m. The inner diameter is 0.2 m for the lower loop seal, and 0.15 m for the upper loop seal and internal loop

seal. The diameter of cyclone of the AR and FR is 0.15 m. Both the downcomers have a diameter of 0.05 m. The particles are silica sand with a density of 2600 kg/m3 and an average size of 0.2 mm, respectively. Details are found in Kolbitsch et al.48 in numerical simulations of chemical loop combustion system. A grid-independent study is first performed to investigate the effect of mesh size on the model predictions. Uniform grids of different sizes (coarse grids = 14 86, medium grids = 22 120 and finer grids = 28 178) are tested in the AR. Figure 3 shows the profile of concentration of particles along height for three different grids in the AR. For three different grids, all simulations show the concentration of particles increases from the inlet, reaches maximum, and then decreases along riser height. The difference of simulations using three different grids is obvious. It is found that the finer grids and medium grids give similar resolution. There was no significant difference between the results for the finer and medium grids. However, the coarse grids give a low concentration of particles in the AR. The small differences of simulations between the medium grids and the finer grids indicate acceptable grid convergence. Therefore, the medium grid sizes are used throughout computations to reduce the computation times except otherwise stated. Figure 4b shows the instantaneous concentration of particles at the superficial gas velocities of ug,AR and ug,FR of 2.0 and 2.0 m/ s in the AR and FR. At the beginning of the simulation, the AR and FR are partially preloaded with solids. The cyclones of the AR and FR, internal loop seal, and lower and upper loop seals are also filled to the operating level. Once gas is introduced into the AR and the FR, both beds begin to expand with some particles hitting the top wall and falling down. Some particles close to the first and second cyclones are dragged by gas into the cyclone. At the initial stage, the flow of particles into the cyclone is high, leading to particle accumulation at the apex of the cyclone. Some particles may exit the system from the vortex finder due to strong particleparticle interaction. After t = 7.5 s, the number of particles flowing into the AR cyclone and the FR cyclone begins to decrease. Finally, a macroscopically steady state flow is established, where the input and output rates of particles for each of the flowing units involved are equal. From simulations, two key flow features are captured successfully in the current simulation. The first one is the axial solid segregation. It can be seen that there is axial solid segregation that more particles are mainly in the bottom part of the riser. The concentration of 1405



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Figure 14. Time-averaged concentration of particles in the system. Figure 12. Profile of viscosity of particles in the AR and FR.

Figure 15. Profile of concentration of particle along height in the AR and FR. Figure 13. Distribution of solids viscosity in the internal loop seal, lower and upper loop seals.

particles is low in the top part of the riser. This axial solid segregation was observed in the experiments.48 The second one is the coreannulus flow structure which causes solid backmixing and is characterized by the phenomena that particle concentration is higher near the wall than in the center. Particles always move upward in the center zone but can be either upward or downward near the wall, and gas velocity is higher in the center and lower near the wall. From Figure 4b it can be seen that there are much more particles near the wall than in the center. It also indicates that particles flow upward in the center and almost all of the particles near the wall flow downward. Figure 5 shows the distribution of instantaneous solid mass fluxes at the exit of the air reactor and fuel reactor. The exit mass fluxes of both the air reactor and the fuel reactor are oscillations. In the air reactor, the solids come from the lower loop seal. Particles from the lower loop seal are carried up by gas from the inlet of the air reactor. As particle entrained through the AR, the formation and breaking of clusters appeared continuously in the riser. This changes the exit concentration and velocity of particles, and results in the oscillation of mass fluxes of particles at the exit of the AR. On the other hand, the particles in the FR come from the upper loop seal and the internal loop seal, and discharges into the lower loop seal. Thus, the exit solids mass flux is oscillations in the FR. The standard deviation is calculated and shown in

Figure 5. We see that the standard deviation of solid mass flux in the FR is larger than that in the AR. This means the exit solid mass in the FR significantly relates to the inlet solid mass fluxes from the upper loop seal, the internal loop seal, and the drainage of the fuel reactor. Figure 6 shows the distribution of concentration of particles at three riser heights in the AR and FR. Roughly, the concentration of particles is low in the center regime and high near the walls in the AR and FR. We also found that the concentration of particles is large in the bottom and low at the top, and the concentration of particles decreases with the increase of height from the inlet in the AR and FR. The difference of concentration of particles between the AR and the FR is obvious. The concentration of particles is larger in the FR than that in the AR. In the AR, the particles discharged from the lower loop seal act as the inlet of particles of the AR. In the FR, the solids mass includes two parts, one is from the discharge of the upper loop seal, and other comes from the feed back from the FR cyclone. The particles from these two parts are circulated within the FR. Hence, the solids mass flux in the FR is larger than that in the AR, and the concentration of particles is higher in the FR than in the AR. Figure 7 shows the distribution of axial velocity of particles at three different heights in the AR and FR. Simulations show in both the AR and FR that the axial velocity of particles is positive in the center regime and negative near the walls. This means particles flow upward in the center and flow-down near the walls in the AR and the FR. The circulation of particles is formed in the AR and FR. Comparing to Figure 6, we see that the particles have a high concentration and negative axial velocity in the annulus, 1406



Figure 16. Profile of gas pressure along height in the system.

Figure 17. Profile of instantaneous solid mass flux entering into lower loop seal.

and a low concentration and positive axial velocity in the core of the AR and FR. Figure 8 shows the simulated gas pressure profile of the system. An exponential decay of gas pressure is found in the AR and FR. This is typical for circulating fluidized bed risers and indicates the decrease of solids concentration with height from inlet. The AR, on the other hand, shows a steep pressure change in the bottom region. The upper regions of the AR are, therefore, very lean in solids and no real circulating regime is reached in this case. The reasons for the limited development of the circulating regime are lower gas velocities. The gas pressure is lowest at the exit of cyclones of the AR and FR. From the cyclone of the AR to the upper loop seal, the gas pressure is increased due to the gravity force of particles in the pipeleg and loop seal. The internal loop seal transport particles from the cyclone of the FR to the bottom of the FR. Thus, the gas pressure is increased from the cyclone of the FR to the internal loop seal. The lower loop seal acts as a connector between the AR and the FR. Therefore, gas pressure decreases from the lower loop seal to the AR. The simulated gas pressure drops in the AR and FR are 3.03 and 3.88 (kPa/m), respectively. The high pressure drop in the FR is found. This indicates that the solids concentration is higher in the FR than in the AR. Solids circulation between AR and FR is crucial to operate a CLC reactor. The solids circulation rate in the reactor system can be determined from simulated velocity and concentration of particles. Figure 9 shows the solid mass flux at the exit of AR

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Figure 18. Instantaneous solids mass flux at the exit of upper and internal loop seals.

cyclone, FR cyclone and at the pipeleg between the FR and the lower loop seal. The results clearly indicate very high solids circulation in the system. Owing to the low solids inventory in the AR and the FR respectively, the solids residence time is very short. This implies that the distribution of particle is very narrow. The difference of solid mass flux through the cyclone of the AR and FR is obvious. Roughly, the solid mass flux through the cyclone of FR, GFR, is larger than that GAR from the cyclone of AR to the loop seal. The time-averaged solid mass flux R internal o is G = t+T G(t) dt/To, where To is the time interval. The t calculated time-averaged solid mass fluxes in AR and FR cyclones are given in Figure 9. The time-averaged solid mass fluxes of GAR in the AR and GFR in the FR are = 30.62 and 50.29 kg/m2s. The negative value means particles flow from the cyclone to the downcomer. This means the loading in the AR cyclone and the FR cyclone is different. The ratio of GFR/GAR is 1.64. This ratio depends strongly on the solid circulation in the system. 3.2. Granular Temperature and Viscosity of Particles in the AR and FR. Figure 10 shows the fluctuation kinetic energy of particles as a function of concentration of particles in the AR and FR. Roughly, the granular temperature is decreased with the increase of concentration of particles. The mean granular temperature, θm = (∑N i = 1θi)/N is calculated, where N is the total number of grid cells. The mean value of granular temperature in the AR and FR is given in Figure 10. The calculated mean granular temperature in the AR is larger than that in the FR since the concentration of particles is larger in the FR than in the AR. The particle collisions play an important role in the risers. At the low concentration of particles, the fluctuation kinetic energy is largely due to the collisions of particles. At the high concentration of particles, the granular temperature decreases due to the decrease of the mean free path. When the concentration of particles is close to the packing condition, the granular temperature approaches to zero since particles can hardly move. Figure 11 shows the distribution of granular temperature in the internal loop seal and upper and lower loop seals as a function of concentration of particles. Roughly, the granular temperature decreases with the increase of concentration of particles in the loop seals. The mean value of granular temperature is calculated. In comparison to the granular temperature in the AR and FR shown in Figure 10, the mean granular temperature in the AR and FR is 1 order of magnitude larger than that in the internal 1407



Figure 19. Distribution of solid viscosity in the loop seals.

Figure 20. Distribution of granular temperatures in the loop seals.

loop seal, upper and lower loop seals due to the low gas velocity and high concentration of particles. Figure 12 shows the distribution of viscosity of particles as a function of concentration of particles in the AR and FR. Predicted viscosity of particles increases with the increase of concentration of particles. The mean value of viscosity of particles, μs = (∑N i = 1μs,i)/N is computed. The mean viscosity of particles is 0.00276 in the AR and 0.00271 (kg/(m s)) in the FR. The high viscosity in the AR is due to the high granular temperature shown in Figure 10. Figure 13 shows the distribution of viscosity of particles in the internal loop seal, upper and lower loop seals as a function of concentration of particles. The viscosity of particles increases with the increase of concentration of particles. From eq T1-16, the solids viscosity depends upon the frictional viscosity and kinetic viscosity. From eq T1-17, the kinetic viscosity is given by the sum of the collisional and kinetic contributions. The collisional part is proportional to solid concentration square, while the kinetic part is proportional to concentration of particles. Thus, the collisional component is dominant at the high concentration of particles. From eq T1-18, the frictional viscosity is proportional to the solids pressure which is high at the high concentration of particles. Thus, the frictional viscosity of particles is large at the high concentration of particles. At εs e εs,min, the frictional viscosity is assumed to be zero. On the other hands, both the kinetic and collisional components are proportional to square root of granular temperature. From Figure 11, the granular temperature is low at the high

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Figure 21. Distribution of concentration of particles in the FR and AR.

concentration of particles, and it approaches to zero at the packing. Thus, the predicted solids viscosity is larger at the high concentration of particles in the loop seals due to the contribution of frictional viscosity of particles. 3.3. Effect of Solids Inventory in the AR and FR. The solids inventories in the AR and FR influence the concentration of particles of the AR and FR and the circulating rate of particles between the AR and the FR. Figure 14 shows the timeaveraged concentration of particles at two different solids inventories in the system. For the low solids inventory case, the initial concentration of particles in the AR and FR is 0.24, and the weight of particles in the AR and FR is 16.3 kg. While at the initial solid concentration of 0.5, the weight of particles in the AR and FR is 34.1 kg for the high solids inventory case. With the increase of solids inventory in the system, the concentration of particles in the AR and FR is increased. The high concentration of particles is found at the high solid inventory case. Figure 15 shows the distribution of concentration of particles along height in the AR and FR. Simulations show that for both the low solids inventory and high solids inventory cases the concentration of particles is high at the bottom, and decreases along height. For the low solids inventory case, the highest concentration of particles in the AR occurs at the exit of the lower loop seal. With the increase of solids inventory, the highest concentration of particles moves up. In the FR the variation of concentration of particles depends upon the solids inventory. For the low solids inventory case, the concentration of particles decreases along FR height. The highest concentration of particles occurs at the exit of the internal loop seal. For the high solids inventory case, the concentration of particles is high at the exit of the internal loop seal and the upper loop seal. In the FR, particles come from the internal loop seal and the upper loop seal. This indicates that the performance of the internal loop seal and the upper loop seal affects solids inventory in the FR. From simulations, we also find that the concentration of particles is higher for the high solids inventory than for the low solids inventory in the AR and FR. The pressure balance for the system is important in operations and design. Figure 16 shows the profile of gas pressure at the low and high solids inventories in the system. The fuel reactor is connected to the air reactor via the lower loop seal. It is also connected to the lower part of the riser via the internal loop seal. The gas pressure is lower in the cyclones of the AR and FR 1408



Figure 22. Instantaneous concentration of particles: (a) position = 0.7 m, (b) position = 0.2 m.

Figure 23. Distribution of concentration of particles in the AR and FR.

compared to the loop seals. Therefore, the gas pressure in the fuel reactor should be higher than that in the cyclone, but lower than that in the air reactor. To obtain the right gas pressure in the AR and FR, the pressure drops at the exit from these reactors are controlled simply by adjusting the outlet cross-section area. Simulations give the gas pressure profile for two different solids inventories in the AR and FR. Particles are circulated between the AR and FR through the lower loop seal. The lower loop seal acts as a buffer. The instantaneous solids mass flux entering the lower loop seal from the FR is shown in Figure 17 at two solids inventories. The solids mass flux is negative, which means particles move from the FR to the AR. The large oscillations of solids mass flux are found at the high solids inventory. At the beginning of the simulation the AR and FR is partially preloaded with solids concentration of 0.24 for low solids inventory and 0.5 for high solids inventory, respectively. The loop seals are also preloaded with concentration of particles of 0.5. The fluidized particles in the lower loop seals are at bubbling bed at the superficial gas velocities of 0.2 m/s. After a while (about t = 7.0 s) with increasing gas flow, bubbles form within the bottom region of the lower loop seal. A fluctuating mass flow is released from the lower loop seal due to the breaking of bubbles. These variations in the solid mass flux impact on flow behavior of particles in the AR. Figure 18 shows the instantaneous solids mass flux at the exit of the upper loop seal. Particles move from the upper loop seal to the FR. At the beginning, the upper loop seal is preloaded with a

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Figure 24. Profile axial velocity of particles in the AR and FR.

solids concentration of 0.5. When gas enters from the inlet of the upper loop seal with the superficial gas velocity of 0.05 m/s, particles are fluidized at the bubbling bed. At the same time, particles enter the upper loop seal from the pipeleg of the cyclone of the AR. The large oscillations of solids mass flux at the high solids inventory are found. More particles move from the pipeleg of the cyclone of AR to the FR through the upper loop seal. The instantaneous solids mass flux at the exit of internal loop seal is also shown in Figure 18. The negative solids mass flux means that particles move into the FR from the pipeleg of the cyclone of FR. The time-averaged mass fluxes are 50.65 and 243.87 kg/(m2s) at the low and high solids inventories. These particles are circulated in combination with particles from the upper loop seal in the FR. Thus, more particles are circulated at the high solids inventory, and give a high concentration of particles in the FR. 3.4. Effect of Frictional Stress of Particles. The frictional stress model is important for the EulerianEulerian method as the momentum equations for the solid phase requires closure terms for the solid stresses. Johnson and Jackson26 proposed a model to describe granular flows. The quasi-static model proposed by Srivastava and Sundaresan33 accounts for the strain rate fluctuations. The frictional stress can be determined by considering the stress being composed of the normal contribution and the shear contributions. The frictional pressure is expressed33 !n 1 ∇ 3 us ps, f pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ¼ 1 pffiffiffi ð16Þ pc n 2 sinðψÞ S : S þ θ=ds 2 where pc is the critical pressure in solid phase. The frictional viscosity is 2 !1=ðn 1Þ 3 pffiffiffi ps, f 2ps, f sinðψÞ 5 μs, f ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi2 4n ðn 1Þ pc S : S þ θ=ds ð17Þ where S is the strain rate tensor. The coefficient n is set differently depending on whether the granular assembly is undergoing a dilatation or compaction 8 pffiffiffi > 3 < , ∇ 3 us g 0 n ¼ 2 sinðϕÞ ð18Þ > : 1:03, ∇ 3 us < 0 1409


Industrial & Engineering Chemistry Research At the concentration of particles higher than εs,min the frictional stress occurs, and the stresses are an addition of the kinetic theory and the quasi-static theory, while the frictional stresses no longer play a role at the concentration of particles below εs,min. Figure 19 shows the distribution of solid viscosity as a function of concentration of particles in the lower loop seal and internal loop seal. Both simulations by means of the frictional stress model by Johnson and Jackson26 and Srivastava and Sundaresan33 show the predicted solid viscosity increases with the increase of concentration of particles. At the low concentration of particles, both simulated solid viscosities are close to each other. The difference between simulations using the frictional stress models of Johnson and Jackson and Srivastava and Sundaresan is obvious at the high concentration of particles. The solid viscosity predicted by the frictional stress model of Srivastava and Sundaresan is larger than that using the model of Johnson and Jackson. The mean value of solid viscosity is computed in the lower loop seal and internal loop seal. The mean solid viscosities in the lower loop seal and internal loop seal are 0.01115 and 0.0108 (kg/(m s)) using the frictional stress model of Johnson and Jackson. While they are 0.0101 and 0.0071 (kg/(m s)) by means of the frictional stress model of Srivastava and Sundaresan in the lower loop seal and internal loop seal. This means the frictional stress model proposed by Johnson and Jackson26 leads to the overprediction of solid viscosity in the AR and FR. Figure 20 shows the distribution of granular temperature as a function of concentration of particles in the lower loop seal and internal loop seal. Both simulations using the frictional stress models of Johnson and Jackson26 and Srivastava and Sundaresan33 show that the granular temperature decreases with the increase of concentration of particles. The mean values are calculated. The mean granular temperatures are 4.5 and 3.6 (cm/s)2 using the frictional stresses model of Johnson and Jackson in the lower loop seal and internal loop seal. Using the frictional stresses model of Srivastava and Sundaresan, the mean granular temperatures are 7.1 and 4.4 (cm/s)2 in the lower loop seal and internal loop seal. The granular temperature predicted by the Srivastava and Sundaresan model is larger than that using the Johnson and Jackson model. This means the frictional stress model proposed by Srivastava and Sundaresan underestimates the frictional stress, and gives a large granular temperature in the loop seals. Figure 21 shows the distribution of concentration of particles at two different heights in the FR and AR. Both simulations using the frictional stress model proposed by Johnson and Jackson26 and Srivastava and Sundaresan33 show the concentration of particles is low in the center and high near the walls in the AR and FR. The concentration of particles predicted by the frictional stress model proposed by Srivastava and Sundaresan is larger than that by Johnson and Jackson model. However, the trends are the same. These two frictional stress models give the different distribution of particles in the loop seals, leading to the change of circulation of particles between the loop seals and risers. As a consequence, the distributions of particles in the AR and FR are altered. 3.5. Effect of Vertical Position of the Upper Loop-Seal. The AR and FR of the CLC system are designed as circulating fluidized beds. The upper loop-seal connects the cyclone of AR to the FR. Thus, the vertical position of the upper loop-seal effects the distribution of concentration of particles in the FR. The effect of the vertical position of the upper loop seal on the concentration of particles is shown in Figure 22 at the superficial

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gas velocities of AR and FR of 2.0 and 2.0 m/s. The vertical positions from the bottom of the upper loop seal to the bottom of FR are 0.2 and 0.7 m, respectively. The local concentration of particles at the bottom of the FR is increased with the decrease of vertical position. The concentration of particles in the bottom of AR is also varied due to the change of circulation of the particle from the FR to the AR. Both cases show the concentration of particles is high in the bottom and low at the top of the FR and AR. Figure 23 shows the distribution of concentration of particles at two vertical positions of 0.2 and 0.7 in the AR and FR. Both cases show that the concentration of particles is low in the center, and high near the walls. For two different vertical positions, the trends are the same. The mean value of concentration of particles is calculated. The mean concentration of particles are 0.199 and 0.188 at the vertical position of 0.2 and 0.7 m at the height of z = 0.8 m. At the height of z = 2.1 m, the mean concentration of particles is 0.0476 and 0.0544 at the vertical position of 0.2 and 0.7 m. This means with the reduction of vertical position of the upper loop seal the concentration of particles is increased at the bottom and decreased at the top of the FR. In the AR at the height of z = 1.0 m, the mean concentration of particles is 0.138 and 0.136 at the vertical position of 0.2 and 0.7 m. This indicates the effect of vertical position of the upper loop seal on concentration of particles is negligible in the AR. The vertical position of the upper loop seal affects the distribution of concentration of particles in the FR. Figure 24 shows the profile of axial velocity of particles at two vertical positions of the upper loop seal in the AR and FR. Both simulations show the axial velocity of particles is high in the center and low near the walls in the AR and FR. The axial velocity of particles is positive in the center and negative near the walls in the AR and FR. This indicates particles flow upward in the center, and down-flow near the walls. At the height of z = 0.8 m in the FR, the mean axial velocity of particles is 0.934 and 0.751 m/s at the vertical position of the upper loop seal of 0.2 and 0.7 m. While at z = 2.1 m, the mean axial velocity is 0.871 and 0.953 m/s, respectively. This means with the reduction of vertical position of the upper loop seal the axial velocity of particles is increased in the bottom and decreased at the top of the FR. If the vertical position is too low, particles from the upper loop seal return to the bottom of the FR, and bypass into the lower loop seal. In contrast, when the vertical position is too high, it shortens the residence time of particles in the FR. The difference of simulated axial velocity of particles in the AR is observed at two different vertical positions of the upper loop seal. The trends are, however, the same. Therefore, the vertical position of the upper loop seal is suitable for controlling the distribution of concentration of particles along height of FR.

4. CONCLUSION A two-dimensional CFD simulation with the multiphase Eulerian model incorporating the kinetic theory of solid particles and CSD drag coefficient model is used to simulate flow behavior of gas and particles in a dual circulating fluidized bed system. Two different frictional stress models are considered in the numerical simulations. The distribution of concentration of particles and velocity in the AR and FR is obtained. Flow behavior of particles in the loop seals is predicted. The effect of frictional stress model on flow of particles is analyzed. 1410


Industrial & Engineering Chemistry Research The solid circulation rate increases with the increase of solids inventory in the system. The gas pressure distribution in the FR and AR is affected by the solids inventory and loop seals in a dual circulating fluidized bed system. Bubble behavior and flow patterns simulated in the loop seals are consistent with experimental observations. The concentration of particles in the bottom of the FR increases with the reduction of the vertical position of the upper loop seal. The multiphase model for a dual circulating fluidized bed of chemical looping combustion presented here is the first step of a numerical simulation of such a system. Future effort should extend the model to nonisothermal flow. It is valuable to couple the AR and FR with other components such as the cyclone and loop seals to model the complete loop system since the chemical reaction in the chemical looping reactors is a very important feature in this technology development which can exploit the existing circulating fluidized bed technology.

’ AUTHOR INFORMATION Corresponding Author

*Corresponding author. Tel.: +0451 8641 2258. Fax: +0451 8622 1048. E-mail: [email protected].

’ ACKNOWLEDGMENT This work was supported by Natural Science Foundation of China through Grant Nos. 51176042 and 51121004. ’ REFERENCES (1) Mattisson, T.; Lyngfelt, A.; Leion, H. Chemical-looping with oxygen uncoupling for combustion of solid fuels. Int. J. Greenhouse Gas Control 2009, 3, 11–19. (2) Lyngfelt, A.; Leckner, B.; Mattisson, T. A fluidized-bed combustion process with inherent CO2 separation; application of chemicallooping combustion. Chem. Eng. Sci. 2001, 56, 3101–3113. (3) Ryu, H.; Bae, D.; Jin, G. Chemical-looping combustion process with inherent CO2 separation: reaction kinetics of oxygen carrier particles and 50 kWth reactor design. The World Congress of Korean and Korean Ethnic Scientists and Engineers, Seoul, Korea, 2002; pp 738743. (4) Pfeifer, C.; Rauch, R.; Hofbauer, H. In-bed catalytic tar reduction in a dual fluidized bed biomass steam gasifier. Ind. Eng. Chem. Res. 2004, 43, 1634–1640. (5) Xu, G.; Murakami, T.; Suda, T.; Matsuzawa, Y.; Tani, H. The superior technical choice for dual fluidized bed gasification. Ind. Eng. Chem. Res. 2006, 45, 2281–2286. (6) Seo, M. W.; Goo, J. H.; Kim, S. D.; Lee, S. H.; Choi, Y. C. Gasification characteristics of coal/biomass blend in a dual circulating fluidized bed reactor. Energy Fuels 2010, 24, 3108–3118. (7) Proll, T.; Kolbitsch, P.; Bolhar-Nordenkampf, J.; Hofbauer, H. A novel dual circulating fluidized bed system for chemical looping processes. AIChE J. 2009, 55, 3255–3266. (8) Proll, T.; Mayer, K.; Bolhar-Nordenkampf, J.; Kolbitsch, P.; Mattisson, T.; Lyngfelt, A.; Hofbauer, H. Natural minerals as oxygen carriers for chemical looping combustion in a dual circulating fluidized bed system. Energy Procedia 2008, 1, 27–34. (9) Kolbitsch, P.; Bolhar-Nordenkampf, J.; Proll, T.; Hofbauer, H. Operating experience with chemical looping combustion in a 120 kW dual circulating fluidized bed (DCFB) unit. Int. J. Greenh. Gas Con. 2010, 4, 180–185. (10) Alexander, C.; Nuria, R.; Craig, H.; Monica, A.; Mariusz, Z.; Borja, A.; Georgios, K.; Gunter, S.; Carlos., A. J. Experimental validation of the calcium looping CO2 capture process with two circulating fluidized bed carbonator reactors. Ind. Eng. Chem. Res. 2011, 50, 9685–9695.

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Computational Fluid Dynamic Simulation Based Cluster Structures

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