2026-10-13T08:21:03Z https://www.scidb.cn/oai

10.57760/sciencedb.Partic.00038 2024-10-11T18:17:10Z

2024-10-11 Study of biomass gasification in an industrial-scale dual circulating fluidized bed (DCFB) using the Eulerian-Lagrangian method doi:10.57760/sciencedb.partic.00038 en Dual circulating fluidized bed (DCFB) has emerged as an efficient reactor for biomass gasification due to its unique feature of high gas-solid contact efficiency and separated reactions in two reactors, yet the understanding of complex in-furnace phenomena is still lacking. In this study, biomass gasification in an industrial-scale DCFB system was numerically studied using a multiphase particle-in-cell (MP-PIC) method featuring thermochemical sub-models (e.g., heat transfer, heterogeneous reactions, and homogeneous reactions) under the Eulerian-Lagrangian framework. After model validation, the hydrodynamics and thermochemical characteristics (i.e., pressure, temperature, and species) in the DCFB are comprehensively investigated. The results show that size-/density-induced segregation makes solid fuels concentrate on the bed surface. Interphase momentum exchange leads to the continuous decrease of the gas pressure axially. In the gasifier and combustor, the lower heating value (LHV) of the gas products is 5.56 MJ/Nm3 and 0.2 MJ/Nm3 and the combustible gas concentration (CGC) is 65.5% and 1.86%, respectively. The temperature in the combustor is about 100 K higher than that in the gasifier. A higher solid concentration results in a smaller value of particle heat transfer coefficient (HTC). The HTCs range from 50 to 150 W/(m2 K) for a solid concentration larger than 0.3 in the combustor while the HTCs range from 100 to 200 W/(m2 K) in the gasifier. The Reynolds number of biomass particles is two orders of magnitude larger than that of the sand particle. The numerical results shed light on the reactor design and process optimization of biomass gasification in DCFBs. Dual fluidized bed; Biomass gasification; Numerical simulation; MP-PIC; Heat transfer coefficient Jiahui Yu Shuai Wang Kun Luo Debo Li Jianren Fan PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/https://doi.org/10.1016/j.partic.2023.02.018 Science Data Bank