Performance prediction and optimization of hydrogenation feed pump based on particle swarm optimization – least squares support vector regression surrogate model

IF 5.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Engineering Applications of Computational Fluid Mechanics Pub Date : 2024-02-22 DOI:10.1080/19942060.2024.2315985

Yanpi Lin, Liang Li, Shunyin Yang, Xiaoguang Chen, Xiaojun Li, Zuchao Zhu

引用次数: 0

Abstract

Due to high power consumption and low energy efficiency of the hydrogenation feed multistage pump, conducting structural optimization design and reducing energy losses for this pump is necessary. I...

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基于粒子群优化的加氢进料泵性能预测与优化--最小二乘支持向量回归代用模型

由于加氢进料多级泵功耗高、能效低，因此有必要对该泵进行结构优化设计并减少能量损失。I...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Engineering Applications of Computational Fluid Mechanics ENGINEERING, MULTIDISCIPLINARY-ENGINEERING, MECHANICAL

CiteScore

10.60

自引率

14.80%

发文量

109

审稿时长

3.4 months

期刊介绍： The aim of Engineering Applications of Computational Fluid Mechanics is a continuous and timely dissemination of innovative, practical and industrial applications of computational techniques to solve the whole range of hitherto intractable fluid mechanics problems. The journal is a truly interdisciplinary forum and publishes original contributions on the latest advances in numerical methods in fluid mechanics and their applications to various engineering fields including aeronautic, civil, environmental, hydraulic and mechanical. The journal has a distinctive and balanced international contribution, with emphasis on papers addressing practical problem-solving by means of robust numerical techniques to generate precise flow prediction and optimum design, and those fostering the thorough understanding of the physics of fluid motion. It is an open access journal.