CFD simulation of a fluidized bed reactor for biomass chemical looping gasification with continuous feedstock

Energy Conversion and Management 201 (2019) 112143

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CFD simulation of a fluidized bed reactor for biomass chemical looping gasification with continuous feedstock

T

⁎

Zhenwei Lia,b,1, Hongpeng Xua,b,1, Wenming Yanga,b, , Anqi Zhoua,b, Mingchen Xua,b a b

Sembcorp-NUS Corporate Laboratory, 1 Engineering Drive 2, 117576, Singapore Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, 117575, Singapore

A R T I C LE I N FO

A B S T R A C T

Keywords: Biomass gasification Chemical looping gasification Hydrogen production Fluidized bed Computational fluid dynamics

Integrating the gasification process with the chemical looping technology presents a promising route for biomass conversion with the objective to obtain high quality syngas without air separation. In this study, the biomass gasification with iron-based oxygen carrier and continuous feedstock in the bubbling fluidized bed (BFB) fuel reactor has been investigated based on the computational fluid dynamics (CFD). The solid phases including fuel and oxygen carriers are modeled based on the pseudo-fluid assumption. The numerical model integrates the multi-fluid model and the chemical reaction models involving the decomposition and gasification of biomass and the heterogeneous reactions between gases and metal oxides. The predicted time-varying outlet concentrations of five gas components agree well with the experimental data from the literature. The impacts of the mixing and segregation behaviors between two solid phases on the gas composition distribution are analyzed. The effects of operation temperature, fuel feeding rate and steam content on the chemical looping gasification (CLG) performance are also investigated. The concentrations of CO and H2 as well as the gas yield and gasification efficiency increase while the concentrations of hydrocarbons and CO2 decrease with the escalating temperature because of the facilitation of higher temperature on the endothermic reactions. Raising the feeding rate of biomass leads to a higher gasification efficiency with more valuable syngas but a lower carbon conversion efficiency due to the relatively lower OC-fuel ratio. The gasification atmosphere containing 10–50% of steam also brings remarkable enhancements on the H2 concentration, gas yield and gasification efficiency.

1. Introduction The growing concerns about the fossil fuel shortages and global warming crisis have triggered global efforts to increase the use of renewable energy and reduce the emissions of anthropogenic greenhouse gases. Biomass is regarded as one of the promising alternatives to address these issues thanks to its renewability, abundant availability and carbon neutral characteristic [1,2]. The utilization of biomass can be very extensive and generating valuable syngas through the gasification process is undoubtedly a favorable energy conversion technology [3,4]. The gasifying agents providing the oxygen source for biomass gasification not only can be gaseous agents including air, pure oxygen (O2), steam (H2O), carbon dioxide (CO2) [5–8], but also can be solid particles such as metal oxides, which serve as the oxygen carriers (OC) in the novel technology named chemical looping gasification (CLG) [9,10]. Previous researchers indicated that air-blown gasifiers produce low quality syngas due to the dilution of air, so that high purity oxygen from

an energy intensive air separation units (ASU) is usually required for high quality syngas production, which results in high capital cost and energy penalty in the gasification system [11,12]. Unlike the conventional gasification technologies, a CLG system usually consists of two interconnected reactors: a fuel reactor (FR) and an air reactor (AR), with the oxygen carriers circulating between them. The recycling of OC can save the cost of oxygen production and avoid the direct contact between fuel and air, thus eliminating both the potential generation of thermal NOx and the air dilution to syngas [13]. The external recirculation of hematite also functions as the heat carrier which is able to provide the gasification-required heat in the FR after being heated up in the AR [14]. As an innovative technology with such advantages, CLG has gained the interests of more and more researchers and has been tested with various biomass fuels such as microalgae [15], pine sawdust [16], wheat straw [17], rice straw [18] and rice husk [19], together with different oxygen carriers including iron-based materials [15–17], combined Fe-Cu oxides [18] and manganese ore [19]. Zeng et al. [20]

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Corresponding author at: Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, 117575, Singapore. E-mail address: [email protected] (W. Yang). 1 These authors contributed equally to this work. https://doi.org/10.1016/j.enconman.2019.112143 Received 29 July 2019; Received in revised form 30 September 2019; Accepted 1 October 2019 0196-8904/ © 2019 Elsevier Ltd. All rights reserved.

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Nomenclature bi C Cd ds ess E fc g0,ss G I¯ k0 Keq ṁ m MW n Nu P Pr r ro → R R Re Ro S0 T

t → v X Y

stoichiometric factor for reaction i gas concentration, mol/m3; relative volume fraction drag coefficient particle diameter, m coefficient of restitution activation energy, kJ/mol carbon fraction radial distribution function gas yield, Nm3/kg identity matrix or tensor pre-exponential factor, 1/s equilibrium constant consumption rate, kg/(m3·s) mass, kg molecular weight, kg/kmol reaction order Nusselt number pressure, Pa Prandtl number reaction rate, m/s grain radius, m momentum transfer, m/s universal gas constant, J/(mol·K) Reynolds number oxygen carrying capacity initial surface area, m2/m3 temperature, K

time, s velocity, m/s conversion of solid mass fraction of species

Greek letters α βsg γΘm ε0 εs η Θs λ μ ρm ρ τ¯ Φls

volume fraction the fluid-solid exchange coefficient collisional dissipation, kJ/(m3·s) initial porosity of the particle volume fraction of solid efficiency granular temperature bulk viscosity, Pa·s shear viscosity, Pa·s molar density, mol/m3 density, kg/m3 stress tensor energy loss to the fluid, kJ/(m3·s)

Subscripts g i, j p, q ox red s

investigated the biomass self-moisture CLG process in a fixed bed reactor and found a noticeable increase in the gas yield owing to the moisture content. Huang et al. [21] carried out the contrast experiments: biomass pyrolysis with quartz sand as bed materials and biomass gasification in the presence of natural hematite in a bubbling fluidized bed (BFB) fuel reactor. Results showed that the oxygen source provided by the oxygen carriers can convert more carbon into syngas and the decrease of tar content also suggested the catalysis of oxygen carriers on tar cracking. Wei et al. [22] performed the CLG process using pine sawdust as fuel and synthesized Fe2O3/Al2O3 as oxygen carrier in a 10 kWth interconnected circulating fluidized bed reactor. It was demonstrated that the concentrations of CO, H2 and CH4 increased with the increasing of temperature and the optimal biomass feeding rate was found to obtain the highest cold gas efficiency. The continuous operation of biomass CLG was further scaled up to a 25 kWth prototype composed of a high velocity fluidized bed as an air reactor and a BFB as the fuel reactor as reported in Ge et al. [23]. A significant improvement of carbon conversion efficiency was observed with the temperature in the range of 800–900 °C and the optimal steam-to-biomass ratio was found at 1.0 for higher gas yield while maintaining a high efficiency. Larsson et al. [24] utilized 12% ilmenite as the catalyst mixing with silica sand in a 2–4 MWth dual fluidized bed (DFB) gasifier and achieved ~50% decrease in the yield of tar, accompanied with the undesirable reduction in the cold gas efficiency and the heating value of the gas products. It was also emphasized that the impact of adding ilmenite showed a high dependence upon the operating conditions of the DFB gasifier. Therefore, more efforts are required for the industrial scale and commercialization of the biomass CLG technology [13]. The computational fluid dynamics (CFD), as a useful approach to analyze the interaction between hydrodynamics and chemical kinetics, has been extensively employed to provide detailed information for the operational optimization and scale-up of the chemical looping combustion (CLC) system [25,26]. May et al. [27] developed CFD models for fuel and air reactor of the 1 MWth CLC pilot plant and obtained good

gas species or component phases oxidized form reduced form solid

agreement towards experimental measurements, for the pressure in the FR as well as the gas composition and temperature in the AR. Meanwhile, several numerical investigations regarding the biomass gasification have been reported recently. Luo et al. [28] developed a CFD model to simulate a dual fluidized bed system for biomass gasification, in which they carried out a comparison of a hybrid EMMS drag model and the Gidaspow drag model. Yang et al. [29,30] incorporated the CFD-DEM coupling model with heat transfer and chemical reactions to study the particle-scale behaviors and explore the effects of bubble dynamics for the biomass gasification process in the fluidized bed. Ostermeier et al. [31] performed the coarse-grained CFD-DEM simulation of biomass gasification to investigate the evolution of the wood pellet with size of 6 mm and obtained reasonable prediction of the gasifier behavior and performance. The significance and effectiveness of CFD in the study of multiphase chemical looping systems as well as the biomass gasification process have also attracted increasing attention among the research and exploration of the CLG process. Wang et al. [32] implemented a CFD simulation of coal char gasification in a fuel reactor in order to investigate the influence of operating parameters on CLG performance and gas products. It was concluded that a smaller OC particle size and a lower operating velocity would reduce the syngas production during the CLG process. Li et al. [33] employed the Eulerian multiphase approach to simulate the biomass CLG process, where the thermal degradation of microalgae played an essential role in the fixed bed (FB) fuel reactor. With the consideration of the two-step pyrolysis and iron-steam reactions, the model presented in [33] was well validated by comparing the predicted time-varying concentrations of various gas species with the experimental data of Liu et al. [15]. Nonetheless, the BFB reactor with the key advantages of excellent heat and mass transfer, high degree of mixing and ease of scale-up is widely applied for chemical looping gasification [34]. Although the continuous operation of biomass gasification through chemical looping is of great importance for its development and commercialization, few reports on the numerical investigations of CLG 2

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expressed as

process with continuous feedstock of biomass have been previously presented. In this study, a numerical simulation is conducted to investigate the CLG performance with the sawdust of pine being consecutively fed into the BFB fuel reactor and reacting with the iron-based oxygen carriers. The predicted results of the Eulerian multiphase model integrated with the chemical kinetics including pyrolysis, gasification and metal oxide reduction are compared with the measured values from the experimental study [21]. The influences of the particle behaviors such as mixing and segregation between different phases in the CLG system are analyzed. The validated model is then applied to further evaluate the effects of operation temperature, biomass feeding rate and steam content on the biomass CLG performance.

∂ (αs ρs → vs ) + ∇ ·(αs ρs →→ vs vs ) ∂t g + = −αs ∇p + ∇ ·τ¯s + αs ρs→

n

Rrs + ṁ rs → vrs − ṁ sr → vsr ) ∑ (→

(5)

r=1

The stress tensor for the granular solid phase can be obtained by T τ¯s = −ps I¯ + μs αs (∇→ vs + ∇→ v s ) + αs λs (∇ ·→ vs ) I¯

(6)

where ps represents the solid pressure, μs is the granular viscosity. The fluid-solid momentum exchange term is the opposite number of the solid-fluid momentum, βgs = −βsg . The Gidaspow drag model [36] as a combination of the Wen and Yu model [37] and the Ergun equation [38] is adopted in this work. The drag coefficient is given as

2. Methodology 2.1. Details of the experimental study

→

→

⎧150 αs (1 − αg ) μg + 1.75 ρg αs | vs − vg | , αg ≤ 0.8, ⎪ ds αg ds2 βsg = ⎨ αs αg ρg | → vs − → vg | −2.65 3 C αg , αg > 0.8 ⎪ 4 d ds ⎩

The experimental data to be used for simulation are provided by Huang et al. [21], in which the continuous feedstock of biomass went through the chemical looping gasification process in the presence of oxygen carrier. The BFB reactor has a length of 1000 mm and an inner diameter of 60 mm. A porous quartz plate loading the metal oxide particles is placed at the height of 300 mm, thus the simulated reaction zone is considered to be in height of 700 mm. The reactor was heated to the desired operating temperature, after which the pine sawdust was continuously fed from the top and entered the BFB reactor through a drop tube. The oxygen carrier employed was natural hematite with 90 wt% Fe2O3 as the reactive component. Table 1 summarizes the detailed physical properties and operating parameters of the CLG experimental study. The ultimate and proximate analyses of the pine sawdust (dry basis) are listed in Table 2.

(7)

where

Cd =

24 [1 + 0.15(αg Re)0.687] αg Re

(8)

The solid stress accounting for the collision between particles is given as [39]:

ps = αs ρs Θs + 2ρs (1 + ess ) αs2 g0, ss Θs

(9)

where g0, ss represents the radial distribution function at contact and is expressed as

g0, ss = [1 − (αs / αs,max )1/3]−1

2.2. The CFD model

(10)

The solid viscosity is given as The Eulerian approach has been applied to describe the gas and solid phases in the fluidized bed reactor. The present work is performed based on the Eulerian multiphase model. Three phases were taken into consideration in this model, including two solid phases for biomass and oxygen carriers and one gas phase. The governing equations describing mass, momentum, energy and species transport are solved for each phase as summarized below [35]. The continuity equation for phase q is written as

∂ (αq ρq ) + ∇ ·(αq ρq→ vq ) = ∂t

μs =

2 4 ⎡1 + g0, ss αs (1 + ess ) ⎤ 5 ⎣ ⎦

(ṁ pq − ṁ qp)

λs =

(1)

p=1

n

(2)

Table 1 Simulated fuel reactor properties [21].

∂ (αg ρg → vg ) + ∇ ·(αg ρg →→ vg vg ) ∂t n

∑

→ (Rsg + ṁ sg → vsg − ṁ gs → vgs )

s=1

(3)

→ where Rsg = βsg (→ vs − → vg ) is the drag term. The fluid stress tensor is calculated as T τ¯g = αg μg (∇→ vg + ∇→ v g ) + αg λ g (∇ ·→ vg ) I¯

(13)

where the collisional dissipation is

where Yiq is the mass fraction and i, j denote different species. The conservation equation of momentum for the gas phase is written as

g + = −αg ∇p + ∇·τ¯g + αg ρg→

(12)

τs: (∇→ us ) = γΘm + Φls

m

∑ ∑ (ṁ ijqp − ṁ jipq) p=1 j=1

4 Θ 1/2 αs ρs ds g0, ss (1 + ess ) ⎛ s ⎞ 3 ⎝π⎠

An equilibrium between the production and dissipation of the random kinetic energy is assumed for the calculation of the granular temperature, which is

where αq represents the volume fraction of the qth phase, ṁ pq is the mass transfer rate from the pth phase to the qth phase. The transport equation for each species is given as

∂ (αq ρq Yiq) + ∇ ·(αq ρq→ vq Yiq) = ∂t

(11)

and the bulk viscosity of solids is obtained by

n

∑

10ρs ds Θs π 4 Θ 1/2 αs ρs ds g0, ss (1 + ess ) ⎛ s ⎞ + 5 π 96 αs (1 + ess ) g0, ss ⎝ ⎠

(4)

The conservation equation of momentum for the sth solid phase is 3

Description

Value

Height of the computational domain of the reactor Inner diameter of the reactor Inner diameter of the drop tube Flow rate of Ar from the bottom of the reactor Mass flow rate of biomass from the drop tube Mean diameter of sawdust Mass of the oxygen carrier Mean diameter of oxygen carrier Temperature maintained by the furnace Operation pressure

700 mm 60 mm 20 mm 1500 L/h 0.12 kg/h 0.34 mm 150 g 0.215 mm 840 °C 1 atm

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Table 2 Ultimate and proximate analysis of pine sawdust (dry basis) [21]. Ultimate analysis (wt%) C 48.44

γΘm =

H 6.21

12(1 − ess2 ) g0, ss ds π

Proximate analysis (wt%) O 45.29

N 0.05

S 0.01

Volatiles 84.82

Ash 0.60

19.80

(14) 2.3.2. Char gasification

Φls = 3βs Θs

(15)

The solid-solid exchange coefficient K s1 s2 between the two solid phases is expressed as [40]:

3(1 + ess )(π /2) α s1 α s2 ρs1 ρs2 (d s1 + d s2 )2g0, ss → = | vs1 − → vs2| 2π (ρs1 d s31 + ρs2 d s32 )

C + CO2 → 2CO

(R3)

C + H2O → CO + H2

(R4)

The kinetic model of Everson et al. [44] is adopted for the char gasification rate, which is given as

(16)

ṁ Char = ρs εs

The conservation equation of energy is written as

∂p ∂ + τ¯q: ∇ ·→ (αq ρq hq) + ∇ ·(αq ρq→ vq − ∇ ·→ qq + Sq + vq hq) = αq ∂t ∂t

Fixed carbon 14.58

pyrolysis.

ρs αs2 Θ3/2 s

and the dissipation in fluid is

K s1 s2

LHV (MJ/kg)

(Qpq)

p=1

ri =

(17) where hq represents the specific enthalpy of the qth phase, Sq denotes qq is the source term for enthalpies because of the chemical reactions, → the heat flux, Qpq represents the heat transfer between gas and solid phases:

Qpq = hpq Ai (Tp − Tq)

ki Ki Pi 1 + Ki Pi + Kj Pj

(21)

where i represents the reactant CO2 or H2O, j represents the product CO or H2, respectively. 2.3.3. Water-gas-shift (WGS) reaction

(18) CO + H2O → CO2 + H2

where hpq (=hqp ) is the volumetric heat transfer coefficient between the pth phase and the qth phase and is related to the Nusselt number Nus in the case of granular flows, which is calculated based on the Gunn correlation [41]:

(R5)

The homogeneous WGS reaction is taken into consideration in the CLG process and its reaction rate is written as [45]

1 −E / RT r = −k 0 ⎛⎜e−E / RT CH0.5 C − e CH2O CCO⎞⎟ 2 CO2 K eq ⎝ ⎠

Nus 2 0.7 1/3 = (7 − 10αf + 5α f2 )(1 + 0.7Re0.2 s Pr ) + (1.33 − 2.4αf + 1.2α f )Res

Pr1/3

(20)

where ε0 is the initial porosity, S0 represents the initial surface area of char, and r is written as

n

∑

S0 r (1 − X )2/3 1 − ε0

7

where k 0 = 2.17 × 10 K eq = exp( −4.33 + 4577.8/ T ) .

(19)

1/s,

(22)

E = 192.9 kJ/mol,

and

2.3.4. Metal oxide reduction

2.3. Chemical reaction kinetic model The chemical reactions taking place in the BFB fuel reactor are complicated not only due to the complex thermal degradation process of biomass which could result in numerous different products [42], but also because of the high uncertainty to determine the products generated from the partial oxidation of the fuel by the oxygen carriers [1]. In the present study, the following reaction mechanisms were introduced to investigate the biomass CLG in the BFB fuel reactor.

(R1)

Tar → Woodgas(CH4,C2H4,CO,CO2,H2,H2O) + Tarinert

(R2)

(R6)

C2H4 + 12Fe2O3 → CO + CO2 + H2 + H2O + 8Fe3O4

(R7)

CO + 3Fe2O3 → CO2 + 2Fe3O4

(R8)

H2 + 3Fe2O3 → H2O + 2Fe3O4

(R9)

The partial oxidation of hydrocarbons (CH4 and C2H4) into CO and H2 in the biomass CLG process is suggested by both the experimental

2.3.1. Pyrolysis A two-step model considering the biomass devolatilization and tar cracking was used for the biomass pyrolysis [33,42]. Biomass → Char + Woodgas(CH4,C2H4,CO,CO2,H2,H2O) + Tar

CH4 + 9.75Fe2O3 → 0.25CO + 0.5H2 + 0.75CO2 + 1.5H2O + 6.5Fe3O4

Table 3 Mass fraction of the products from biomass pyrolysis. Component

The mass fraction of the products from the primary pyrolysis (R1) and secondary pyrolysis (R2) are determined by the proximate and ultimate analyses of the pine sawdust [21] and are listed in Table 3. It is assumed that the tar generated from biomass degradation would further decompose into syngas and inert tar [43]. The reaction rates of both pyrolysis reactions are expressed in the form of Arrhenius law, i.e., k 0 exp(−Ea/ RT ) , with pre-exponential factor k 0, pri = 4.13 × 106 1/s and activation energy Ea, pri = 112.7 kJ/mol for primary pyrolysis, k 0, sec = 9.55 × 104 1/s and Ea, sec = 123.3 kJ/mol for secondary

Char CH4 C2H4 CO CO2 H2 H2O Tar Tarinert

4

Mass fraction Primary pyrolysis

Secondary pyrolysis

0.147 0.078 0.037 0.456 0.183 0.016 0.010 0.073 –

– 0.102 – 0.650 0.128 0.020 – – 0.100

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inside the reactor with the initial height of 26 mm. Pure argon is introduced from the bottom of the reactor as fluidizing gas with the flow rate of 1500 L/h. When the bed materials are fluidized, pine sawdust and balance gas begin to enter the reactor through the drop tube inlet, with the flow rate of 0.12 kg/h and 200 L/h, respectively. The gas outlet is set at the top of the reactor and assumed to be at atmospheric pressure. A constant temperature of 840 °C is assumed for the walls of the reactor. A two-dimensional axisymmetric mesh is used for the fuel reactor. Fig. 1a displays the lower portion of the computational domain. The mesh sensitivity analysis, similar to the published work [47], was first implemented using two different grid sizes. In order to maintain the numerical stability, the time step size was also reduced by a factor of five for the fine mesh. Fig. 1b shows the comparison of the outlet gas concentrations versus time using fine and coarse mesh in the first 5 min. It can be seen that the discrepancy of the results obtained from two sets of grids is not evident. Therefore, the coarse mesh is chosen in the subsequent simulations because of the significantly lower computational cost.

studies [15] and numerical investigations [33]. It is also noted that the main component of the reduced metal oxides is Fe3O4 in Huang et al. [21], thus the further reduction of oxygen carrier into FeO is not taken into account. The OC reduction rates are calculated based on the shrinking core model (SCM) for the heterogeneous reactions [46]. The conversion degree of oxygen carriers is used to describe the progress of the reactions [47].

X=

mox − m mox − mred

(23)

Differentiating Eq. (21) gives the conversion rate of the metal oxide, which is related to the mass loss of the OC particles.

dX 1 dm 1 dm = = dt mox − mred dt R o mox dt

(24)

where R o = (mox − mred )/ mox represents the oxygen carrying capacity. The expressions of the consumption rates of the combustible gases by oxygen carriers are summarized in Li et al. [33]. The reaction rates of H2 and CO are given as

ṁ i =

ki =

3MWFe2O3 ⎞ ki R o 2/3MW ρ εs ⎜⎛YFe O + YFe3O4 × ⎟ (1 − X ) i 2MWO2 s ⎝ 2 3 2MWFe3O4 ⎠

(25)

3. Results and discussion

3bi k 0, i e−Ei / RT (Ci − Ci, eq) ρm ro

3.1. Model validation

(26)

Fig. 2 shows the evolution of volume fraction and velocity vectors of oxygen carriers and biomass with time. Since sawdust was continuously fed into the reactor through the drop tube when the desired temperature was reached and the oxygen carriers were well fluidized, the time that marks the start of biomass input is considered to be time zero. At the time t = −1 s, the bed height reaches about 40 mm and the regions of low solid volume fraction can be observed, which demonstrates the formation of bubbles and the reasonably good fluidization state. The instantaneous contour of biomass at t = 1 s displays the successful entry of biomass into the reactor, while the corresponding velocity vector shows the upward motion above the inlet of these particles, which is ascribed to their low solid density and the relatively high velocity of the rising gas stream from the bottom of the reactor. The continuous feedstock of sawdust will experience instantaneous thermal decomposition once they enter the reactor, releasing volatile gases and tar at

where i stands for H2 and CO, bH2 = bCO = 3, k 0,H2 = 2.3 × 10-3 1/s, k 0,CO = 6.2 × 10-4 1/s, EH2 = 24 kJ/mol, ECO = 20 kJ/mol. The consumption rate of CH4 is written as

ṁ CH4 =

12MWFe2O3 ⎞ YCH4 kCH4 R o ρ εs ⎜⎛YFe O + YFe3O4 × M ⎟ (1 − X ) YCH4, TGA 2MWO2 s ⎝ 2 3 8MWFe3O4 ⎠ WCH4

(27) −4

where kCH4 = 5.33 × 10 1/s, YCH4, TGA = 0.1. The consumption rate of C2H4 can be obtained with the same coefficients according to the reaction kinetics provided in [47]. 2.4. Initial and boundary conditions and grid independence The oxygen carriers which contain 90 wt% of Fe2O3 are packed

Fig. 1. Computational domain and mesh sensitivity analysis. (a) Schematic of the BFB reactor and the magnified lower and upper portions of the coarse computational meshes. (b) Comparison of the outlet gas concentrations versus time using a fine and a coarse mesh. 5

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Fig. 2. Instantaneous volume fractions and velocity vectors (m/s) of oxygen carriers and biomass. The oxygen carriers were first fluidized by argon flow from the bottom of the reactor at 1500 L/h. Biomass was continuously fed from the drop tube into the reactor from the time t = 0 s, with a feeding rate of 0.12 kg/h and operating temperature of 840 °C.

the experimental system behaves more like CLC owing to the extremely high OC-fuel ratio, generating high concentration of CO2 and low concentrations of CH4, C2H4, CO and H2 in the outlet. In the meantime, CO2 and H2O are favorable gasifying agents for the char conversion into CO and H2, resulting in low char mass in the first 5 min. The lattice oxygen availability decreases as the mass fraction of Fe2O3 is gradually descending, hence the partial oxidation of fuel begins to dominate in the reactor, leading to the increase of combustible gases concentrations and decrease of CO2 concentration. Correspondingly, the consumption rate of char declines as the generation of gasifying agents decreases, so that the char mass within the reactor climbs to a higher value as the reaction proceeds. In the last 15 min, all gas concentrations are basically stable over time and the mass variations of OC and char within the reactor are not obvious as the remaining Fe2O3 gradually decreases to near zero. Therefore, the CLG fuel reactor can be considered to be in a quasi-steady state after 30 min of the reaction stage. Fig. 5 shows the instantaneous distributions of gas compositions at

such temperature and remaining char. Although a negligible amount of char may be entrained to the freeboard area at a relatively low velocity, as recognized in the subsequent contours and vectors, the bed surface of the emulsion phase is mainly in the range of 40–60 mm, which matches the bed height described in the experimental study [21]. Comparing the phase contours of oxygen carriers and biomass (Fig. 2a and b) it can be observed that the motion behaviors of OC and fuel particles in the bed are different and fluctuating, resulting in distinct and unstable bed surfaces for the two solid phases. The dense region of oxygen carriers is usually in the lower portion of the reactor, while the fuel particles are mainly floating near the inlet of drop tube because of the progressively lower density, making the upper portion the primary contact area between the metal oxides and the volatile gases produced from pyrolysis as well as the CO and H2 generated from char gasification. Such segregation of two particle phases was also observed in the numerical studies of Wang et al. [32] and Armstrong et al. [48]. On the other hand, Mahalatkar et al. [47] indicated that the insufficient contact between fuel and OC particles leads to partial combustion, which is undoubtedly a weakness in chemical looping combustion but could be considered as an advantage for syngas production in the CLG process. Fig. 3 shows a comparison of the calculated gas concentrations of five gas components and the measured values as a function of time [21]. The model predictions provide an excellent agreement with the experimental data. The significant variations of gas concentrations with reaction time (especially H2 and CO2) in the CLG process are captured in a reasonable manner. The concentrations of all the combustible gases (CH4, C2H4, CO and H2) display a slowly increasing trend during the test, while the CO2 concentration decreases rapidly with time in the first 20 min, after which the change gradually becomes gentle. In the fuel reactor of the CLG process, metal oxide reduction reactions as well as char gasification play an important role in the syngas compositions. The mass variations of different solid particles within the reactor are shown in Fig. 4, where the evolutions of hematite and magnetite mass are represented in the form of line while the change in char mass is expressed in the form of columns. The use of histogram for time-averaged char mass per 5 min is to eliminate the strong fluctuation due to its production during the devolatilization of continuous feedstock and its consumption through heterogeneous reactions, thus better illustrating the evolution of char mass over time. In the initial stage of the CLG process, hematite as the bed material undoubtedly far outweigh the progressive feeding of sawdust, so that

Fig. 3. Simulated concentrations of synthesis gas in comparison with the measured data of Huang et al. [21], with biomass feeding rate of 0.12 kg/h and temperature of 840 °C. 6

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fluidizing agent. Fig. 7 shows the compositions and total yield of syngas along with the carbon conversion efficiency (ηc), gasification efficiency (η), and lower heating value (LHV, MJ/Nm3) as the function of operation temperature. They are obtained by the following equations [15,21]:

12(CCO + CCO2 + CCH4 + 2CC2H4 ) Gv × 100% 22.4fC

(28)

LHV = 12.6CCO + 10.8CH2 + 35.9CCH4 + 63.5CC2H4

(29)

ηC =

η=

LHV × G V × 100% Qb

(30)

where Gv (Nm3/kg) is the total yield of five gas species (i represents CH4, C2H4, CO, CO2 and H2), Ci is the mole fraction of the corresponding gas component in the flue gas, fC is the carbon content of biomass, Qb (MJ/kg) is the lower heating value of the sawdust. As can be seen in Fig. 7, an obvious increase from 47.55% to 54.27% of CO and decrease from 14.79% to 8.29% of CO2 composition are quite remarkable as the temperature increases from 740 °C to 890 °C. This is because higher temperature enhances the endothermic Boudouard reaction (R3) and restrains the exothermic reaction (R8), facilitating the CO generation and weakening the conversion of CO into CO2 simultaneously. The enhancement of endothermic steam gasification (R4) by the high temperature also leads to a steady increase of H2 concentration. However, the concentrations of the hydrocarbons display a slight decrease with the increasing temperature. Similar results were presented in the experimental study [49]. As CH4 and C2H4 oxidations by OC are endothermic reactions, they may consume more of these two gas species at higher temperature. In addition, it is observed that the increase in temperature results in a decrease of H2/CO ratio, which is consistent with the inference that the H2/CO ratio is adjustable within a certain temperature range in biomass CLG as stated in [49]. Furthermore, both the gasification efficiency and carbon conversion efficiency as well as the gas yield increase with the escalating temperature since the endothermic biomass conversion including pyrolysis and char gasification are significantly enhanced at higher temperature. The evolution of LHV, on the other hand, is indistinctive due to the combined effect of decreasing hydrocarbon gases and increasing CO composition. The evolution of oxygen carrier conversion X and conversion rate dX/dt at various operation temperature are shown in Fig. 8. It can be seen that at each moment, the OC conversion at higher temperature is always above that at lower temperature in the modelling time of 30 min, attributing to the enhancement of OC reduction reactions at high temperature. Their differentiation, on the other hand, shows the same temperature-related results in the first 10 min but then turns into the opposite relationship after the intersection, indicating that the conversion rate of oxygen carrier firstly increases with the rising temperature but descends faster due to the rapidly decreasing mass fraction of Fe2O3.

Fig. 4. Mass of oxygen carriers and char in the fuel reactor as a function of time.

t = 1 min and t = 10 min. As expected, all of the product gas species only occur around and above the biomass inlet compared with the corresponding volume fraction contours in Fig. 2, which means that the metal oxide reduction reactions mainly take place in the upper portion of the bed, with the reaction rates displayed in Fig. 6. It can be seen from Fig. 5 that the highest mole fractions of CH4, C2H4, CO and H2 are in the emulsion region because of the rapid devolatilization of biomass. Another reason accounting for the peak concentrations of CO and H2 relies on the endothermic char gasification with CO2 and H2O in the emulsion phase. The locations of the peak mole fractions of CO2 and H2O, on the other hand, are slightly higher than those of other gas components. This is because the combustible gases are consumed by the metal oxides and more CO2 and H2O are produced in addition to the thermal degradation of biomass. Furthermore, the increase of mole fractions of CH4, C2H4, CO and H2 and decrease of mole fractions of CO2 and H2O with time can also be observed by comparing the left hand side with the right hand side of the contour for each gas species. This can be well explained by Fig. 6, which demonstrates that the reaction rates of OC reduction are also declining with the reaction proceeding in the biomass CLG reactor.

3.2. Effects of operation temperature One of the essential operating conditions for biomass CLG is the reactor temperature, which can influence the thermal conversion of biomass and the heterogeneous reactions between OC and the combustible gases. Previous researchers have pointed out that a CLG system is better to be operated in the temperature range of 650 °C to 1000 °C, below which the CLG reactions cannot occur, and exceeding which the oxygen carriers are likely to sinter [22]. It is also reported that the pores among the granules might be blocked due to the fusion of gasification ash at higher temperature, which is unfavorable for maintaining the reactivity of the oxygen carriers [15]. Hence, the range of 740–890 °C was selected to investigate the effects of operation temperature on biomass CLG, with the feeding rate of 0.12 kg/h and argon as the

Fig. 5. Instantaneous contours of gas species mole fractions at t = 1 min (left) and t = 10 min (right). 7

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Fig. 6. Reaction rates (kmol/(m3·s)) of OC reduction at t = 1 min (left) and t = 10 min (right).

attributed to the OC reduction reactions (R6–R9) since the biomass CLG is a partial oxidization process. When the sawdust feeding rate is relatively small, the fuel is more prone to be fully converted into CO2 and H2O by the excessive lattice oxygen provided by metal oxides. As the biomass feeding rate increases, while the inventory of natural hematite is kept constant, the reactions between the increasing volatiles released from biomass pyrolysis and the available lattice oxygen provided by oxygen carriers become more incomplete, resulting in the rise of the combustible gases. In the meantime, the increasing char content in the reactor also benefits both the Boudouard (R3) and steam gasification (R4) reactions, stimulating the generation of CO and H2 as well as the consumption of CO2. As seen from Fig. 9, the gasification efficiency and LHV display a steady upward trend whereas the carbon conversion efficiency declines slightly as the fuel feeding rate increases. The descent of carbon conversion can be explained by the decreasing OC-fuel ratio as the lattice oxygen would be less sufficient due to the larger amount of biomass entering the reactor. That is to say, part of the residual char might not be fully converted into carbonaceous gas, thus lowering the carbon conversion efficiency [22]. The variations of gas compositions, especially the growth of CO and H2 as well as the decline of CO2, lead to an increase of LHV. Meanwhile, the change in gas yield is insignificant, although it is reported that increasing the OC-fuel ratio would contribute to an increase of the gas yield in the experimental study with a fixed bed reactor [20]. This is because the amount of OC inventory can be considered fairly larger than that of the consecutive feedstock of biomass in the BFB reactor, meaning that the OC-fuel ratio is kept at a relatively high value, so that the gas yield could be maintained by consuming more lattice oxygen from the oxygen carriers. Therefore, the increasing feeding rate gives a higher gasification efficiency in the biomass CLG process. Fig. 10 illustrates the evolution of oxygen carrier conversion X and conversion rate dX/dt with various biomass feeding rate. It is observed that the increase of biomass feeding rate significantly promotes the conversion of oxygen carrier owing to the enhanced redox reactions

Fig. 7. Effects of operation temperature on biomass CLG performance.

Fig. 8. Evolution of OC conversion at different operation temperature.

3.3. Effects of biomass feeding rate Different from the goal of thorough combustion in biomass CLC process, the intention of biomass CLG is to produce synthesis gas as much as possible. Thus, it is of great importance to keep the OC-fuel ratio at a low value to prevent the complete oxidation of fuel to CO2 and H2O. In the present study, changing the amount of oxygen carrier particles may affect the fluidization inside the fuel reactor. Therefore, the influences of OC-fuel ratio on CLG were investigated by altering the biomass feeding rate from 0.09 kg/h to 0.18 kg/h, while the inventory of bed materials was kept as a constant (150 g), with the temperature of 840 °C and argon as the fluidizing agent. The compositions and total yield of syngas, along with the carbon conversion efficiency (ηc), gasification efficiency (η) and LHV as the function of biomass feeding rate are shown in Fig. 9. The CO and H2 concentrations increase smoothly while the CO2 concentration declines rapidly with the escalation of biomass feeding rate. This can be

Fig. 9. Effects of biomass feeding rate on biomass CLG performance. 8

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gases is considered to be the optimum steam content in this study. As a consequence of the gas distribution evolution, the LHV of the gas product shows a small decrease and is retained at around 14.2 MJ/Nm3 with the increase of steam content. The evolution of oxygen carrier conversion X and conversion rate dX/dt with various biomass feeding rate are displayed in Fig. 12. As can be seen, the conversion of oxygen carriers is significantly enhanced owing to the substantial growth of the combustible gases yield with the addition of steam as gasification agent. The time variations of their differentiation also suggest the faster consumption rate of natural hematite as the reactant in the atmosphere with higher steam ratio.

4. Conclusion A transient CFD model for simulation of biomass chemical looping gasification with continuous feedstock in a bubbling fluidized bed fuel reactor has been developed. By integrating the Eulerian multiphase model with the chemical kinetic models including pyrolysis of biomass, gasification of char, WGS reaction and OC reduction reactions, this model is able to provide a relatively good prediction of the time-varying outlet concentrations of five gas components in comparison with the measured values from the experimental study [21]. The results demonstrate the continuous feedstock of pine sawdust and the mixing and segregation behaviors between fuel and OC particle phases, which have strong impacts on the gas composition distribution as well as the evolution of the solid particles in the CLG system. The effects of various operation temperature, biomass feeding rate and steam content on the biomass CLG performance are analyzed. It is found that increasing the temperature facilitates the endothermic reactions, leading to an increase of CO and H2 concentrations and the decrease of CH4, C2H4 and CO2 concentrations. The gas yield and gasification efficiency also increase with the escalating temperature but the change in LHV is indistinctive as a result of the varying gas compositions. Increasing the biomass feeding rate, on the other hand, gives a lower OC-fuel ratio, resulting in higher concentrations of the combustible gases and lower concentrations of CO2 and H2O. Hence, the LHV and gasification efficiency smoothly ascends but the carbon conversion efficiency slightly descends due to the less sufficient lattice oxygen as larger amount of biomass enters the reactor. The addition of steam as the gasification agent significantly improves the biomass CLG performance in terms of H2 concentration, gas yield, carbon conversion efficiency as well as the gasification efficiency. No obvious enhancement is observed with the introduction of excess steam, thus 50% in the fluidizing gases is considered to be the optimum steam content in order to avoid the potential energy consumption.

Fig. 10. Evolution of OC conversion at different biomass feeding rate.

(R6–R9) between natural hematite and the larger amount of combustible gases generated from biomass pyrolysis and char gasification. The time variations of their differentiation also indicate that the OC conversion rate was firstly accelerated with the increase of biomass feeding rate but then descended faster due to the rapid consumption of the reactant natural hematite.

3.4. Effects of steam content Steam is considered as an effective gasification agent in the CLG process to promote the thermochemical conversion of solid fuel into valuable gaseous products, especially for the generation of H2-rich syngas. Moreover, according to the previous study [33], the presence of steam can efficiently prevent Fe3O4 from being further reduced to FeO/ Fe, which is beneficial for keeping the reactivity of the oxygen carriers [15]. Additionally, the use of water vapor as gasification agent is more in line with the needs of industrial fluidized beds [50]. Hence, the influence of steam content on the biomass CLG performance was investigated by varying the proportion of steam in the range of 0–75% in the fluidizing gas, whose total flow rate was kept at 1500 L/h, with the fuel feeding rate of 0.12 kg/h and temperature of 840 °C. Fig. 11 shows the compositions and total yield of syngas along with the carbon conversion efficiency (ηc), gasification efficiency (η) and LHV as the function of steam content. As can be seen, the H2 concentration increases from 20.83% in pure argon atmosphere to 29.84% with 10% of steam contained in the fluidizing agents, and then smoothly climbs to 31.86% as the steam content reaches 75% mainly due to the steam gasification reaction (R4). Correspondingly, the concentrations of CH4, C2H4, CO display a slight downtrend with the increasing steam ratio. Such results are consistent with the previous work [33] and other publications [23,50]. With the increase of steam content, the reaction rate of WGS (R5) increases, leading to an escalation in the mole fraction of H2 and CO2 in the outlet. However, the increment of CO2 is smaller than the increments of CO and H2 owing to the char gasification reactions, hence the relative concentration of CO2 shows a descent firstly but then increases slightly as more steam is introduced into the fluidized bed reactor. It is observed that the gas yield is elevated with the increasing steam content and maintained at around 1.28 Nm3/kg as the steam content exceeds 50% in the fluidizing gases. Simultaneously, both the gasification efficiency and carbon conversion efficiency present an apparent ascent and then becomes stable at around 91.0% and 99.5%, respectively. Moreover, several studies have pointed out that excess steam would increase the energy penalty and promote the conversion of CO into CO2 [15,23,50], indicating that further increasing the steam ratio in the fluidizing gases may not lead to an improvement but a diminishment on the biomass CLG performance, thus 50% in the fluidizing

Fig. 11. Effects of steam content on biomass CLG performance. 9

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Fig. 12. Evolution of OC conversion at different steam content.

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