RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge
The axle bridge plays a crucial role in the bogie of low-floor light rail vehicles, impacting operational efficiency and fuel economy. To minimize the total cost of the structure and turning of axle bridges, an optimization model of structural and turning parameters was built, with the fatigue life,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/14/3/273 |
| _version_ | 1797240063618187264 |
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| author | Xiaoke Li Wenbo Xing Qianlong Jiang Zhenzhong Chen Wenbo Zhao Yapeng Xu Yang Cao Wuyi Ming Jun Ma |
| author_facet | Xiaoke Li Wenbo Xing Qianlong Jiang Zhenzhong Chen Wenbo Zhao Yapeng Xu Yang Cao Wuyi Ming Jun Ma |
| author_sort | Xiaoke Li |
| collection | DOAJ |
| description | The axle bridge plays a crucial role in the bogie of low-floor light rail vehicles, impacting operational efficiency and fuel economy. To minimize the total cost of the structure and turning of axle bridges, an optimization model of structural and turning parameters was built, with the fatigue life, maximum stress, maximum deformation, and maximum main cutting force as constraints. Through orthogonal experiments and multivariate variance analysis, the key design variables which have a significant impact on optimization objectives and constraints (performance responses) were identified. Then the optimal Latin hypercube design and finite element simulation was used to build a Radial Basis Function (RBF) model to approximate the implicit relationship between design variables and performance responses. Finally, a multi-island genetic algorithm was applied to solve the integrated optimization model, resulting in an 8.457% and 1.1% reduction in total cost compared with the original parameters and parameters of sequential optimization, proving the effectiveness of the proposed method. |
| first_indexed | 2024-04-24T18:01:29Z |
| format | Article |
| id | doaj.art-53fbc9a5a90e42a2a2b6e4517c9ced1d |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-04-24T18:01:29Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-53fbc9a5a90e42a2a2b6e4517c9ced1d2024-03-27T13:54:17ZengMDPI AGMetals2075-47012024-02-0114327310.3390/met14030273RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle BridgeXiaoke Li0Wenbo Xing1Qianlong Jiang2Zhenzhong Chen3Wenbo Zhao4Yapeng Xu5Yang Cao6Wuyi Ming7Jun Ma8Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaHenan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaHenan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaCollege of Mechanical Engineering, Donghua University, Shanghai 201620, ChinaLuoyang TiHot Railway Machinery Manufacturing Co., Ltd., Luoyang 471000, ChinaHenan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaHenan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaHenan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaThe axle bridge plays a crucial role in the bogie of low-floor light rail vehicles, impacting operational efficiency and fuel economy. To minimize the total cost of the structure and turning of axle bridges, an optimization model of structural and turning parameters was built, with the fatigue life, maximum stress, maximum deformation, and maximum main cutting force as constraints. Through orthogonal experiments and multivariate variance analysis, the key design variables which have a significant impact on optimization objectives and constraints (performance responses) were identified. Then the optimal Latin hypercube design and finite element simulation was used to build a Radial Basis Function (RBF) model to approximate the implicit relationship between design variables and performance responses. Finally, a multi-island genetic algorithm was applied to solve the integrated optimization model, resulting in an 8.457% and 1.1% reduction in total cost compared with the original parameters and parameters of sequential optimization, proving the effectiveness of the proposed method.https://www.mdpi.com/2075-4701/14/3/273structural optimizationturning parameter optimizationaxle bridgeRadial Basis Functionoptimal Latin hypercube design |
| spellingShingle | Xiaoke Li Wenbo Xing Qianlong Jiang Zhenzhong Chen Wenbo Zhao Yapeng Xu Yang Cao Wuyi Ming Jun Ma RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge Metals structural optimization turning parameter optimization axle bridge Radial Basis Function optimal Latin hypercube design |
| title | RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge |
| title_full | RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge |
| title_fullStr | RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge |
| title_full_unstemmed | RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge |
| title_short | RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge |
| title_sort | rbf based integrated optimization method of structural and turning parameters for low floor axle bridge |
| topic | structural optimization turning parameter optimization axle bridge Radial Basis Function optimal Latin hypercube design |
| url | https://www.mdpi.com/2075-4701/14/3/273 |
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