Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm
Jet fish pumps are efficient hydraulic machinery for fish transportation. Yet, the complex flow phenomenon in it is the major potential risk for damage to fish. The dangerous flow phenomena for fish, such as radial pressure gradient and exposure strain rate, are usually controlled by the structural...
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| Format: | Article |
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MDPI AG
2022-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/11/4104 |
| _version_ | 1797493514877009920 |
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| author | Maosen Xu Guorui Zeng Dazhuan Wu Jiegang Mou Jianfang Zhao Shuihua Zheng Bin Huang Yun Ren |
| author_facet | Maosen Xu Guorui Zeng Dazhuan Wu Jiegang Mou Jianfang Zhao Shuihua Zheng Bin Huang Yun Ren |
| author_sort | Maosen Xu |
| collection | DOAJ |
| description | Jet fish pumps are efficient hydraulic machinery for fish transportation. Yet, the complex flow phenomenon in it is the major potential risk for damage to fish. The dangerous flow phenomena for fish, such as radial pressure gradient and exposure strain rate, are usually controlled by the structural parameters of jet fish pumps. Therefore, the injury rate of fish can be theoretically decreased by the structural optimization design of jet fish pumps. However, there is a complex nonlinear relation between flow phenomena and key structural parameters. To solve this problem, the present paper established a complex mapping between flow phenomena and structural parameters, based on computational fluid dynamics and a back-propagation neural network. According to this mapping, an NSGA-II multi-objective genetic algorithm was used to optimize the structure of jet fish pumps. The results showed that the optimized jet fish pumps could reduce the internal radial pressure gradient, exposure strain rate and danger zone to 40%, 12.5% and 50% of the pre-optimization level, respectively. Therefore, the optimized jet fish pump could significantly reduce the risk of fish injuries and keep the pump efficiency at a high level. The results could provide a certain reference for relevant structural optimization problems. |
| first_indexed | 2024-03-10T01:21:05Z |
| format | Article |
| id | doaj.art-8ee5a664cfa846cda0e5b34274f976d5 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T01:21:05Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-8ee5a664cfa846cda0e5b34274f976d52023-11-23T14:00:24ZengMDPI AGEnergies1996-10732022-06-011511410410.3390/en15114104Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic AlgorithmMaosen Xu0Guorui Zeng1Dazhuan Wu2Jiegang Mou3Jianfang Zhao4Shuihua Zheng5Bin Huang6Yun Ren7College of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Metrology and Measurement Engineering, China Jiliang University, Hangzhou 310018, ChinaCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Metrology and Measurement Engineering, China Jiliang University, Hangzhou 310018, ChinaZhejiang Nanyuan Pump Industry Co., Ltd., Huzhou 313219, ChinaSchool of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaSchool of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaZhijiang College, Zhejiang University of Technology, Hangzhou 310024, ChinaJet fish pumps are efficient hydraulic machinery for fish transportation. Yet, the complex flow phenomenon in it is the major potential risk for damage to fish. The dangerous flow phenomena for fish, such as radial pressure gradient and exposure strain rate, are usually controlled by the structural parameters of jet fish pumps. Therefore, the injury rate of fish can be theoretically decreased by the structural optimization design of jet fish pumps. However, there is a complex nonlinear relation between flow phenomena and key structural parameters. To solve this problem, the present paper established a complex mapping between flow phenomena and structural parameters, based on computational fluid dynamics and a back-propagation neural network. According to this mapping, an NSGA-II multi-objective genetic algorithm was used to optimize the structure of jet fish pumps. The results showed that the optimized jet fish pumps could reduce the internal radial pressure gradient, exposure strain rate and danger zone to 40%, 12.5% and 50% of the pre-optimization level, respectively. Therefore, the optimized jet fish pump could significantly reduce the risk of fish injuries and keep the pump efficiency at a high level. The results could provide a certain reference for relevant structural optimization problems.https://www.mdpi.com/1996-1073/15/11/4104jet fish pumpstructural optimizationpressure gradientexposure strain rateBP neural networkNSGA-II algorithm |
| spellingShingle | Maosen Xu Guorui Zeng Dazhuan Wu Jiegang Mou Jianfang Zhao Shuihua Zheng Bin Huang Yun Ren Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm Energies jet fish pump structural optimization pressure gradient exposure strain rate BP neural network NSGA-II algorithm |
| title | Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm |
| title_full | Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm |
| title_fullStr | Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm |
| title_full_unstemmed | Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm |
| title_short | Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm |
| title_sort | structural optimization of jet fish pump design based on a multi objective genetic algorithm |
| topic | jet fish pump structural optimization pressure gradient exposure strain rate BP neural network NSGA-II algorithm |
| url | https://www.mdpi.com/1996-1073/15/11/4104 |
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