Biomass steam gasification in bubbling fluidized bed for higher-H2 syngas: CFD simulation with coarse grain model

被引:62
作者
Qi, Tian [1 ,2 ]
Lei, Tingzhou [1 ,2 ,3 ]
Yan, Beibei [1 ]
Chen, Guanyi [1 ]
Li, Zhongshan [1 ,4 ]
Fatehi, Hesameddin [5 ]
Wang, Zhiwei [2 ,3 ]
Bai, Xue-Song [5 ]
机构
[1] Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300072, Peoples R China
[2] Henan Key Lab Biomass Energy, Zhengzhou 450008, Henan, Peoples R China
[3] Henan Acad Sci, Zhengzhou 450008, Henan, Peoples R China
[4] Lund Univ, Div Combust Phys, S-22100 Lund, Sweden
[5] Lund Univ, Div Fluid Mech, S-22100 Lund, Sweden
基金
中国国家自然科学基金;
关键词
Numerical simulation; CGM; Fluidized bed; Biomass steam gasification; EULERIAN-LAGRANGIAN SIMULATION; WOOD GASIFICATION; HIGH-TEMPERATURE; PARTICLE METHOD; DEM SIMULATION; HEAT-TRANSFER; CHARCOAL BED; FLOW; VALIDATION; COMBUSTION;
D O I
10.1016/j.ijhydene.2019.01.146
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
A comprehensive coarse grain model (CGM) is applied to simulation of biomass steam gasification in bubbling fluidized bed reactor. The CGM was evaluated by comparing the hydrodynamic behavior and heat transfer prediction with the results predicted using the discrete element method (DEM) and experimental data in a lab-scale fluidized bed furnace. CGM shows good performance and the computational time is significantly shorter than the DEM approach. The CGM is used to study the effects of different operating temperature and steam/biomass (S/B) ratio on the gasification process and product gas composition. The results show that higher temperature enhances the production of CO, and higher S/B ratio improves the production of H-2, while it suppresses the production of CO. For the main product H-2, the minimum relative error of CGM in comparison with experiment is 1%, the maximum relative error is less than 4%. For the total gas yield and H-2 gas yield, the maximum relative errors are less than 7%. The predicted concentration of different product gases is in good agreement with experimental data. CGM is shown to provide reliable prediction of the gasification process in fluidized bed furnace with considerably reduced computational time. (C) 2019 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
引用
收藏
页码:6448 / 6460
页数:13
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