CFD-DEM investigation on effects of particle size distribution and gas temperature on minimum fluidization velocity of pyrites

被引:0
|
作者
Long, Wei [1 ]
Ji, Jingbo [1 ]
Zeng, Wei [2 ]
Han, Zhiming [2 ]
Zhang, Hao [1 ,3 ,4 ]
An, Xizhong [1 ]
Jiang, Shengqiang [5 ]
机构
[1] Northeastern Univ, Sch Met, Key Lab Ecol Met Multimet Mineral, Minist Educ, Shenyang 110819, Peoples R China
[2] Wengfu Chem Co, Wengfu Grp Co Ltd, Dazhou 550500, Fuquan, Peoples R China
[3] Minist Educ, Engn Res Ctr Frontier Technol Low carbon Steelmaki, Shenyang 110819, Peoples R China
[4] Inst Low carbon Frontier Technol Steelmaking, Shenyang 110819, Peoples R China
[5] Xiangtan Univ, Sch Mech Engn & Mech, Xiangtan 411105, Peoples R China
来源
PARTICUOLOGY | 2025年 / 96卷
基金
中国国家自然科学基金;
关键词
Pyrite; Particle size distribution; CFD-DEM; Minimum fluidization velocity; PARTICULATE SYSTEMS; ELEVATED-TEMPERATURE; BED EXPANSION; SILICA SAND; SIMULATION; PRESSURE; REACTOR; FLOW;
D O I
10.1016/j.partic.2024.11.009
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The multiphase reactive flow behavior of pyrites in fluidized roasters is closely related to particle size distribution (PSD) and gas temperature. The coupled computational fluid dynamics-discrete element method (CFD-DEM) is used to stress the effect of PSD and gas temperature on the minimum fluidization velocity (Umf). Firstly, the accuracy of the model is verified via the previously well-established correlations. Then, the influence of four types of PSD (Gaussian-type, Mono-type, Flat-type and Binary-type) and three temperatures on Umf is explored. Numerical results show that the Umf for the Flat-type PSD is the smallest among the four while the one for the Mono-type PSD is the largest. The minimum fluidization velocities for the Mono-type and Gaussian-type PSD share quite similar values. With the same PSD, increasing the gas temperature results in a decrease in the minimum fluidization velocity. Finally, predictive correlations for the minimum fluidization velocity of the gas-solid fluidized bed reactors are established based on the numerical results. (c) 2024 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:244 / 255
页数:12
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