The rapid devolatilization of biomass in chemical looping combustion could form a local plume of volatiles, reducing contact between volatiles and oxygen carriers and thus lowering gas conversion. Hence, a novel concept called volatiles distributor (VD) has been recently proposed to enhance the mixing between the volatiles and oxygen carriers. However, the configurations of VD have significant effects on its performance. To optimize the configurations of VD, the impact of VD with different configurations has been investigated with respect to the mixing behaviors and the pathways of volatiles in this work using computational fluid dynamics (CFD) modeling with an Eulerian-Eulerian two-fluid model coupled with a two-step EMMS/bubbling drag model. Comparison to experimental results from a cold-flow fluidized bed demonstrates that the CFD model can provide quantitative predictions for the vertical pressure profiles and reasonable trends of horizontal gas distributions of the fluidized bed under various conditions. Conditions varied were the superficial gas velocity, the percentage of the simulated volatiles, primary air distributor, and configurations of VD. The CFD simulations of both original and new designs reveal that the performance of the VD can be improved by reducing the open area of the distribution holes of the VD near the injection port and increasing it further away from the injection port. An optimal configuration is proposed to achieve an even distribution of volatiles and avoid the leakage of volatiles from the bottom of the VD.

Achieving high volatiles conversion is crucial to biomass chemical looping combustion. Challenges arise from rapid devolatilization of biomass and limited biomass injection ports, resulting in volatiles with insufficient contact with oxygen carriers in fluidized beds. A concept called volatiles distributor (VD) has recently been proposed and investigated in a cold-flow fluidized bed, which shows excellent performance in achieving an even distribution of volatiles over the cross section. To deeply understand VD's impact on hydrodynamics behaviors, pioneering three-dimensional full-loop cold-flow CFD simulations were conducted using an Eulerian multiphase granular model. Three drag models, i.e., Gidaspow, Filtered, and two-step EMMS/bubbling, were evaluated against experimental data. While all models perform well in bubbling fluidization, the two-step EMMS/bubbling model excels in turbulent fluidization. Additionally, CFD simulations reveal improved mixing between volatiles and bed materials with VD, highlighting its efficiency in addressing incomplete conversion of high-volatile fuels like biomass in fluidized bed systems.

In reactor-scale CFD modeling of biomass pyrolysis with thermally-thick particles, zero-dimensional (0D) models coupled with lumped kinetics are commonly used, as they are simple and computationally efficient. However, intra-particle heat transfer, which cannot be directly implemented in 0D models, has significant effects on pyrolysis behaviors of thermally-thick biomass particles. Additionality, lumped kinetics usually fails to predict detailed composition of pyrolysis products. To overcome these issues, a widely-used one-dimensional (1D) model that can directly incorporate intra-particle heat transfer was employed with a detailed pyrolysis kinetics in this work to develop a corrected 0D (Cor-0D) model for accurate CFD modeling of biomass pyrolysis inside thermally-thick particles. Correction coefficients of external heat transfer, particle diameter, and pyrolysis reactions were introduced by comparing predictions of the 1D model with those of the 0D model quantitatively to reflect the effects of respective factors. The comparison demonstrates that if correction coefficients are properly determined, predictions of the developed Cor-0D model are in good agreement with experimental data as well as those of the employed 1D model under various conditions, while the 0D model overestimates mass loss rate and particle heating rate for thermally-thick biomass particles. Considering that correction coefficients are case dependent and determination of their values are tedious, artificial neural network (ANN) was used to correlate correction coefficients as functions of convective heat transfer coefficient, particle size, gas temperature, moisture content, and particle’s dimensionless temperature to derive an ANN-Cor-0D model. Results show that the ANN-Cor-0D model has the same performance as the Cor-0D model.

The multi-fluid model has been widely used to study heat transfer between gas and solid in bubbling fluidized beds. However, zero-dimensional (0D) model has been commonly used. The model assumes a uniform tem-perature distribution, which is only reasonable for thermally-thin particles (Biot number (Bi) < 1). However, one-dimensional (1D) model considering intra-particle temperature inhomogeneity inside particles is difficult to be implemented in multi-fluid model. To solve this issue, a corrected coefficient is introduced to quantitively feature the effects of intra-particle temperature inhomogeneity inside particles on external heat transfer, which forms a corrected 0D model. The corrected coefficient is correlated as a binary function of Bi and dimensionless temperature. The results of particle-scale modeling show that temperature profiles predicted by the corrected 0D model are the same as those of the 1D model for both thermally-thin and thermally-thick particles, while the 0D model overestimates heat transfer between particles and surrounding gas. The corrected 0D model is further implemented in the multi-fluid model to simulate particle cooling and heating process in bubbling fluidized beds. The results predicted by CFD simulations with both the 0D and the corrected 0D models are in good agreement with the experimental data of thermally-thin particles. For both the cooling and heating processes, a significant difference is observed for thermally-thick particles, indicating the importance of considering intra-particle temperature inhomogeneity in multi-fluid modeling. Consistent with the results of particle-scale modeling, the corrected 0D model predicts a smaller heat transfer rate between the gas and solid phases, as compared to the 0D model. Additionally, computational efficiency of the corrected 0D model is comparable to that of the 0D model.

This paper reviews the recent advances in multi-scale computational fluid dynamics (CFD) simulations of biomass pyrolysis in fluidized bed reactors. The interconnection among molecular-scale, particle-scale, CFD cell-scale, and reactor-scale are first introduced, together with the Eulerian-Lagrangian (E-L) and Eulerian multi-fluid model (MFM) frameworks. Then an overview of the theoretical basis and practical applications of four main particle-scale models, i.e, uniform conversion model, progressive conversion model, interface-based model, and corrected uniform conversion model, are highlighted. The coupling of particle-scale models with CFD cell-scale models is discussed, as well as with molecular-scale models. Finally, the perspective of future work to develop reliable and efficient CFD models for simulating biomass pyrolysis in fluidized bed reactors is outlined.

A one-dimensional model with consideration of internal and external heat transfer, particle shrinkage, moisture evaporation, and pyrolysis kinetics is developed to predict biomass torrefaction behaviors. Three different kinetic schemes (i.e. a lump kinetic scheme and two detailed kinetic schemes (Andre ' s Anca-Couce and IngwaldObernberger, 2016, and Debiagi et al., 2018) are evaluated to find the suitable pyrolysis kinetics for biomass torrefaction process. The modeling results are compared with single beechwood particle torrefaction experiments. The results show that the detailed kinetic scheme proposed by Debiagi et al. shows the best performance among the three kinetic schemes, and it can correctly predict particle shrinkage, particle conversion, mass loss history, and biochar C/H/O compositions, while the lump kinetic scheme underestimates torrefaction rates and particle shrinkage degree at low temperature conditions (280-370 degrees C), and the kinetic scheme proposed by Andre ' s and Ingwald underestimates carbon concentration and overestimates the oxygen concentration of torrefied wood at high temperature conditions (370, 400, and 430 degrees C). Therefore, the kinetic scheme of Debiagi et al. is considered to be the most promising kinetics in particle-scale modeling of the torrefaction process. A sensitivity analysis is also performed to evaluate the effects of modeling parameters on modeling results as well as study the control mechanism of torrefaction process. The results show that modeling results are significantly influenced by parameters involved with external and external heat transfer related, boundary conditions, and reaction rate, indicating torrefaction process of large particles is controlled by both internal and external heat transfer, and kinetics.