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首页> 外文期刊>International journal of hydrogen energy >A predictive approach for thermodynamic modeling of solubility in supercritical fluids using genetic algorithm
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A predictive approach for thermodynamic modeling of solubility in supercritical fluids using genetic algorithm

机译:基于遗传算法的超临界流体溶解度热力学模型预测方法

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摘要

The interaction parameter k(ij) used in various mixing rules is not always available. The present work deals with its determination using a group contribution approach which itself is based on group interaction parameters. To date the interaction parameters matrix concerns twelve groups only. Therefore new parameters were determined by optimizing a well defined objective function by means of the genetic algorithm (GAs) and using the Predictive Soave Equation of State (PSEOS) with the van der Waals mixing rule (VDW MR), considering the solubility of organic solutes in supercritical carbon dioxide at elevated pressure ranging from 60 to 350 bar. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:在各种混合规则中使用的交互参数k(ij)并非始终可用。本工作使用基于小组互动参数的小组贡献方法来确定它。迄今为止,相互作用参数矩阵仅涉及十二个组。因此,通过使用遗传算法(GAs)优化定义明确的目标函数,并结合范德华混合规则(VDW MR)使用预测的Soave状态方程(PSEOS),确定了新参数,同时考虑了有机溶质的溶解度在60至350 bar的高压范围内的超临界二氧化碳中。 (C)2017氢能出版物有限公司。由Elsevier Ltd.出版。保留所有权利。

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