Optimization of the impeller for hydraulic performance improvement of a high-speed magnetic drive pump

Author:

Xu Zhenfa12ORCID,Kong Fanyu2,Zhang Kun2,Zhu Han2,Wang Jiaqiong2,Qiu Ning2

Affiliation:

1. School of Mechanical Engineering, Anhui Polytechnic University, Wuhu, China

2. Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, China

Abstract

Magnetic drive centrifugal pumps have compact structure and lower efficiency than ordinary centrifugal pumps. The surrogate-based optimization technique was applied to improve the performance of a high-speed magnetic drive pump with the help of numerical simulations. Eight geometrical parameters of the impeller were considered as the design variable. About 290 samples of impeller were generated by optimal Latin hypercube sampling (OLHS) method, and the corresponding efficiencies of all the impeller samplings were obtained from numerical simulation. The performance test of the prototype pump was carried out, and the experimental results were in good agreement with the numerical simulation results. The hydraulic efficiency at 1.2 Qd of the magnetic drive pump was set as the optimization objective. Using response surface methodology (RSM), surrogate models were established for the objective functions based on the numerical results. The multi-island genetic algorithm (MIGA) was used to optimize the impeller. The hydraulic efficiency of the optimal impeller at rated flow rate was 72.89%, which was 6.23% higher than the prototype impeller.

Funder

Jiangsu Province’s Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Mechanical Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3