LAPSE:2023.1932
Published Article

LAPSE:2023.1932
Optimization Design for the Centrifugal Pump under Non-Uniform Elbow Inflow Based on Orthogonal Test and GA_PSO
February 21, 2023
Abstract
The non-uniform inflow caused by the elbow inlet is one of the main reasons for the low actual operation performance of a centrifugal pump. Orthogonal experiment and GA_PSO algorithm are used to improve the head and efficiency of a centrifugal pump with an elbow inlet based on the method combining numerical simulation and prototype experiment in this paper. The effects of the design parameters, including elbow inlet radius ratio, blade inlet angle, blade number, blade wrap angle, blade outlet angle, impeller outlet diameter, blade outlet width and flow area ratio, on the pump head and efficiency are studied in the orthogonal experiment. The blade inlet angle is the major factor to match the non-uniform inflow and reduce the flow loss in the impeller inlet to contribute to enhancing the pump performance and cavitation characteristics. The particle swarm optimization (PSO) algorithm is optimized by integrating the genetic algorithm (GA), which ensures that the PSO-calculation result avoids falling into the local optimization and the global optimal solution is obtained as quickly as possible. The centrifugal pump with an elbow inlet is optimally designed by the GA_PSO algorithm. According to the performance test results, the efficiency of the optimized pump is 4.7% higher than that of the original pump.
The non-uniform inflow caused by the elbow inlet is one of the main reasons for the low actual operation performance of a centrifugal pump. Orthogonal experiment and GA_PSO algorithm are used to improve the head and efficiency of a centrifugal pump with an elbow inlet based on the method combining numerical simulation and prototype experiment in this paper. The effects of the design parameters, including elbow inlet radius ratio, blade inlet angle, blade number, blade wrap angle, blade outlet angle, impeller outlet diameter, blade outlet width and flow area ratio, on the pump head and efficiency are studied in the orthogonal experiment. The blade inlet angle is the major factor to match the non-uniform inflow and reduce the flow loss in the impeller inlet to contribute to enhancing the pump performance and cavitation characteristics. The particle swarm optimization (PSO) algorithm is optimized by integrating the genetic algorithm (GA), which ensures that the PSO-calculation result avoids falling into the local optimization and the global optimal solution is obtained as quickly as possible. The centrifugal pump with an elbow inlet is optimally designed by the GA_PSO algorithm. According to the performance test results, the efficiency of the optimized pump is 4.7% higher than that of the original pump.
Record ID
Keywords
centrifugal pump, elbow inflow, GA_PSO algorithm, optimization design, orthogonal experiment
Subject
Suggested Citation
Yuan Y, Jin R, Tang L, Lin Y. Optimization Design for the Centrifugal Pump under Non-Uniform Elbow Inflow Based on Orthogonal Test and GA_PSO. (2023). LAPSE:2023.1932
Author Affiliations
Yuan Y: School of Energy and Power, Jiangsu University of Science and Technology, Zhenjiang 212100, China
Jin R: Tianjin Navigation Instruments Research Institute, Tianjin 300131, China
Tang L: Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
Lin Y: School of Energy and Power, Jiangsu University of Science and Technology, Zhenjiang 212100, China
Jin R: Tianjin Navigation Instruments Research Institute, Tianjin 300131, China
Tang L: Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
Lin Y: School of Energy and Power, Jiangsu University of Science and Technology, Zhenjiang 212100, China
Journal Name
Processes
Volume
10
Issue
7
First Page
1254
Year
2022
Publication Date
2022-06-23
ISSN
2227-9717
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Original Submission
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PII: pr10071254, Publication Type: Journal Article
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LAPSE:2023.1932
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https://doi.org/10.3390/pr10071254
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Feb 21, 2023
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