文献类型：期刊文献

英文题名：Numerical simulation of Opposed Multi-Burner gasifier under different coal loading ratio

作者：Xu, Jianliang[1];Zhao, Hui[1];Dai, Zhenhua[1];Liu, Haifeng[1];Wang, Fucheng[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Coal Gasificat & Energy Chem, POB 272, Shanghai 200237, Peoples R China

年份：2016

卷号：174

起止页码：97

外文期刊名：FUEL

收录：;EI(收录号：20160701911162);WOS:【SCI-EXPANDED(收录号:WOS:000370530600012)】；

基金：This work is supported by National Natural Science Foundation of China (21376082) and Shanghai Natural Science Foundation (15ZR1409500).

语种：英文

外文关键词：Numerical simulation; Gasification; OMB; Droplets size; Multiphase flow

摘要：The Opposed Multi-Burner (OMB) gasifier has been widely used in commercial plants throughout China. A comprehensive three-dimensional numerical model is developed for the simulation of an OMB gasifier. In this model, the realizable k-epsilon turbulence model is applied to close the Reynolds-averaged Navier-Stokes equation and the eddy-dissipation-concept model is used to simulate the homogeneous reactions. The coal water slurry (CWS) droplets or particles are described by Lagrangian equation of motion and the evaporation, devolatilization, and heterogeneous reactions processes are modeled. The effect of the coal water slurry atomization on droplets size is also considered. Lastly, the influences of the gasifier coal loading ratio (CLR) on the OMB gasifier performance, particle concentration distribution and temperature distribution have been investigated. The results show that by increasing the gasifier coal loading ratio, the carbon conversion and effective gas yield increase. The temperature distribution in the impinging jet stream can be expressed as a decaying exponential function and the decaying rate corresponds to the particle ratio distribution. Due to the increase of the coal loading ratio, the temperature decaying rate of the impinging up jet stream increases and gas temperature at the top of the gasifier decreases. The numerical results for the OMB gasifier are in good agreement with the industry operation data and observed phenomenon. (c) 2016 Elsevier Ltd. All rights reserved.