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基于Kriging模型的气液两相离心泵优化设计

许继洋 梁淑琪 杨国栋 王彦伟

化学工程2025,Vol.53Issue(4):65-71,7.
化学工程2025,Vol.53Issue(4):65-71,7.DOI:10.3969/j.issn.1005-9954.2025.04.012

基于Kriging模型的气液两相离心泵优化设计

Optimization design of gas-liquid two-phase centrifugal pump based on Kriging model

许继洋 1梁淑琪 2杨国栋 3王彦伟4

作者信息

  • 1. 武汉工程大学机电工程学院湖北省绿色化工装备工程技术研究中心,湖北武汉 430205||河北科技工程职业技术大学 机电工程学院,河北 邢台 054000
  • 2. 郑州理工职业学院机电工程学院,河南 郑州 450000
  • 3. 宇通客车股份有限公司,河南 郑州 450061
  • 4. 武汉工程大学机电工程学院湖北省绿色化工装备工程技术研究中心,湖北武汉 430205
  • 折叠

摘要

Abstract

In order to improve the head and efficiency of high-speed centrifugal pump under gas-liquid two-phase conditions,the high-speed centrifugal pump model Q5H26 was taken as the research object.The effects of different gas content(volume fraction)on the performance of centrifugal pump were analyzed.The results show that the larger the gas content,the lower the head and the efficiency.The parameters of the worm gear and the impeller of the centrifugal pump were analyzed comprehensively and sensitively based on the Kriging model.In order to improve the operating efficiency and head,the parameters of the high-speed centrifugal pump were optimized using the NLPQL algorithm under the gas-liquid two-phase conditions.The numerical simulation of the optimized model was carried out,and the operation efficiency and head of the model pump before and after optimization were compared by experiments.The results show that in the rated working condition,the gas content rate of 10%,the optimized model pump efficiency is increased by 8%,the head is increased by 1.5 m,and the optimization effect is more significant.The results can provide an effective method for improving the performance of the high-speed centrifugal pumps under the conditions of gas-liquid two-phase.

关键词

离心泵/气液两相/Kriging模型/NLPQL算法/优化设计

Key words

centrifugal pump/gas-liquid two-phase/Kriging model/NLPQL algorithm/optimization design

分类

机械制造

引用本文复制引用

许继洋,梁淑琪,杨国栋,王彦伟..基于Kriging模型的气液两相离心泵优化设计[J].化学工程,2025,53(4):65-71,7.

基金项目

国家自然科学基金资助项目(51373186) (51373186)

湖北省教育厅重点科研项目(D20161506) (D20161506)

化学工程

OA北大核心

1005-9954

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