期刊
CHEMICAL ENGINEERING RESEARCH & DESIGN
卷 176, 期 -, 页码 34-48出版社
ELSEVIER
DOI: 10.1016/j.cherd.2021.09.027
关键词
Elastic and inelastic contact models; Flow regime transition; Titania nanoparticle agglomerates; CFD-DEM approach; Conical fluidized bed
This study evaluates the fluidization characteristics of irregularly shaped Titania nanoparticle agglomerates in different flow regimes through experiments and simulations, revealing the differences in prediction accuracy of various models for bed pressure drop and expansion ratio. The comparative results offer promising insights for industrial applications.
The present study evaluates elastic and inelastic contact forces in predicting the fluidization characteristics of irregularly shaped Titania nanoparticle agglomerates in a bench-scale conical fluidized bed. At first, experiments were performed to identify the mutual effects of gas velocity and agglomerate size on the instantaneous pressure, bed pressure drop and bed expansion ratio. Rigid complex-agglomerates (similar to 100-200 mu m) were mainly formed in the partially fluidized regime, while soft simple-agglomerates (similar to 20-70 mu m) were primarily formed in the spouting regime. The simulations were performed through the CFD-DEM approach. The error analysis of results in the partially fluidized regime revealed that the combination of Hertz-Mindlin and Johnson-Kendall-Roberts (HM + JKR) model led to a better prediction of the bed pressure drop and bed expansion ratio than the spring-dashpot (LSD) model. In the transition flow regime, the Hysteretic model led to better results of the instantaneous pressure values than those proposed for other flow regimes. In the spouting flow regime, the HM and Thornton models led to over-estimation of bed pressure drop when compared to the LSD model. The comparative results of this study provide promising new insights into the collision mechanism of polydisperse agglomerates in different flow regimes for industrial aspects. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据