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Direct modeling of voidage at layer inversion in binary liquid-fluidized bed

机译:直接在二元流化床层反演中的空隙建模

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In liquid-fluidized bed chemical and biochemical reactors composed of binary mixtures, peculiar segregation effects can determine layers rich in one or the other component to revert their position in the bed (layer inversion phenomenon), with significant influence on the process performance. In contrast to previous modeling formulation that focused on the simultaneous prediction of the layer inversion velocity and voidage, in the present work two approaches for the direct prediction of the critical voidage are presented, validated and discussed. One is a straightforward extension of a similar model developed for binary gas-fluidized beds (named PSM) and the other one includes more appropriate treatment of the expanded bed conditions typical of liquid-fluidized beds (named ePSM). Both are tested in their prediction capability in comparison with three previously available models, all against experimental values of the inversion voidage, and for float/sink experimental observations available in the literature. Using the simplified PSM formulation the average discrepancy from inversion experiments results considerable (0.097 in voidage units), while with the ePSM it is much smaller (0.052), good in comparison with the others (0.051, 0.086 and 0.033). With dense float/sink experiments the agreement is very good for both PSM and ePSM. Analysis of the effects of the relevant variables on the inversion voidage is carried out, showing how it is possible to derive an inversion map, a universal one for the PSM and one at each composition with ePSM. Finally, the addition to ePSM of the separate calculation of the inversion velocity is shown by comparing the predicted and experimentally observed expansion characteristics of the two solids with velocity. Qualitative matching of trends is found with reasonable quantitative agreement. (C) 2015 Elsevier B.V. All rights reserved.
机译:在由二元混合物组成的液体流化床化学和生化反应器中,独特的偏析效应可以确定富含一种或另一种成分的层,以使其在床中的位置恢复原位(层反转现象),这对工艺性能产生重大影响。与以前的建模公式侧重于层反转速度和空隙率的同时预测相反,在本工作中,提出,验证和讨论了两种直接预测临界空隙率的方法。一个是对为二元气体流化床(称为PSM)开发的类似模型的直接扩展,另一个是对液体流化床(称为ePSM)的典型扩展床条件进行了更适当的处理。与三个先前可用的模型相比,这两个模型的预测能力都经过了测试,均针对反演空隙率的实验值以及文献中提供的浮/沉实验观察。使用简化的PSM公式,反演实验得出的平均差异相当大(空隙单位为0.097),而使用ePSM时,则要小得多(0.052),与其他指标(0.051、0.086和0.033)相比很好。通过密集的浮动/下沉实验,该协议对于PSM和ePSM都非常好。进行了相关变量对反演孔隙度的影响分析,显示了如何能够推导出反演图,PSM通用图和ePSM每种组成图。最后,通过将两种固体的预测和实验观察到的膨胀特性与速度进行比较,可以看出反演速度的独立计算已添加到ePSM中。通过合理的定量协议找到趋势的定性匹配。 (C)2015 Elsevier B.V.保留所有权利。

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