Evaluation of correlations for minimum fluidization velocity (U) in gas-solid fluidization

流态化 球形 阻力 机械 热力学 航程(航空) 指数 物理 统计物理学 数学 材料科学 流化床 几何学 语言学 哲学 复合材料
作者
Aditya Anantharaman,Ray Cocco,Jia Wei Chew
出处
期刊:Powder Technology [Elsevier BV]
卷期号:323: 454-485 被引量:84
标识
DOI:10.1016/j.powtec.2017.10.016
摘要

The minimum fluidization velocity (Umf), defined as the superficial gas velocity at which the drag force of the upward moving gas becomes equal to the weight of the particles in the bed, is one of the most important parameters associated with a fluidized bed system. Specifically, it is the point at which all the particles become suspended. Unsurprisingly, more than a hundred correlations have sprouted since 1950 to enable the prediction of the Umf value. However, discrepancies among the predictions are significant, which limits the utility of each correlation. Accordingly, this study attempts to provide a comprehensive comparison of the Umf values predicted by the correlations available, which are classified into four types depending on the form of the equation and applied to more popular Geldart Groups A, B and D particles. The following observations are highlighted: (i) discrepancies among Umf predictions are presumably attributed to the empirical data-fitting based on limited experimental datasets rather than physical understanding; (ii) correlations involving an empirical coefficient as an exponent exhibit greater discrepancies (up to 6 orders-of-magnitude) in Umf predictions than those without; (iii) predictions for Geldart Group A particles displayed greater discrepancies across categories, due to a lack of understanding of cohesive forces associated with Group A particles; (iv) correlations involving voidage (εmf) and sphericity (φ) exhibit more unphysical trends than those without, presumably due to a limited range of εmf and φ experimentally assessed, hence the inclusion of these two parameters increased the errors associated with these correlations. A mechanistically based correlation may be still intractable at this point, so recommendations are made for future studies on improving the prediction of Umf.
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