基于遗传算法的多相流最优闭合关系选择

S. Mohammadi, M. Papa, E. Pereyra, C. Sarica
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引用次数: 0

摘要

采用遗传算法来确定最佳的封闭关系集,以模拟管道中的多相流行为。这种建模通常是通过使用质量和动量守恒方程的机械方法来完成的。此外,需要一组闭合关系来完成基于实验数据建立的方程组。由于可能存在大量闭包,搜索空间的大小受到组合爆炸问题的影响,通常使用主题专家来选择最佳解决方案。本文提出了一种用R语言实现的遗传算法,用于实现该过程的自动化。初步结果表明,它有能力在合理的时间内选择与人类专家一样好或更好的组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selection of Optimal Closure Relationships for Multiphase Flow using a Genetic Algorithm
A genetic algorithm is used to help determine the best set of closure relationships to model multiphase flow behavior in pipes. This modeling is typically done through a mechanistic approach that uses conservation equations of mass and momentum. In addition, a set of closure relationships are required to complete the system of equations which are developed based on experimental data. Owing to a large number of possible closures, the size of the search space suffers from a combinatorial explosion problem and subject matter experts are often used to select the best solution. This paper presents a genetic algorithm, implemented in R, that is used to automate the process. Preliminary results show that it has the ability to select combinations as good as or better than those of a human expert in a reasonable amount of time.
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