Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm
The equivalent T-stub method is frequently employed in infrastructure projects, including bridge engineering, to simplify bolted connection analysis. However, steel connections remain inherently complex due to nonlinear behavior, cost considerations, and code compliance, framing the design process a...
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| Format: | Article |
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MDPI AG
2025-01-01
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| Series: | Infrastructures |
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| Online Access: | https://www.mdpi.com/2412-3811/10/1/8 |
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| author | Péter Grubits Tamás Balogh Majid Movahedi Rad |
| author_facet | Péter Grubits Tamás Balogh Majid Movahedi Rad |
| author_sort | Péter Grubits |
| collection | DOAJ |
| description | The equivalent T-stub method is frequently employed in infrastructure projects, including bridge engineering, to simplify bolted connection analysis. However, steel connections remain inherently complex due to nonlinear behavior, cost considerations, and code compliance, framing the design process as a discrete structural optimization problem. This research addresses these challenges by presenting a comprehensive calculation framework that combines the finite element method (FEM) and genetic algorithm (GA) to accurately evaluate the structural performance of bolted T-stub configurations. The proposed approach accounts for nonlinear behavior, thereby reflecting realistic structural responses. To enhance the simulation efficiency and reduce the computational time without significantly compromising accuracy, the study introduces a simplified modeling methodology. The effectiveness of the approach is demonstrated through the development and experimental validation of a selected T-stub connection. Furthermore, a parameter sensitivity analysis is conducted to showcase the range of possible outcomes, emphasizing the potential for optimization. Finally, the proposed connections were optimized using GA, highlighting the benefits of structural optimization in achieving efficient and precise designs for steel connections. |
| format | Article |
| id | doaj-art-d6b12c54bc90480b8cf5837e32ba1fc9 |
| institution | Kabale University |
| issn | 2412-3811 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Infrastructures |
| spelling | doaj-art-d6b12c54bc90480b8cf5837e32ba1fc92025-01-24T13:35:23ZengMDPI AGInfrastructures2412-38112025-01-01101810.3390/infrastructures10010008Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic AlgorithmPéter Grubits0Tamás Balogh1Majid Movahedi Rad2Department of Structural and Geotechnical Engineering, Széchenyi István University, 9026 Gyor, HungaryInter-CAD Ltd., 1072 Budapest, HungaryDepartment of Structural and Geotechnical Engineering, Széchenyi István University, 9026 Gyor, HungaryThe equivalent T-stub method is frequently employed in infrastructure projects, including bridge engineering, to simplify bolted connection analysis. However, steel connections remain inherently complex due to nonlinear behavior, cost considerations, and code compliance, framing the design process as a discrete structural optimization problem. This research addresses these challenges by presenting a comprehensive calculation framework that combines the finite element method (FEM) and genetic algorithm (GA) to accurately evaluate the structural performance of bolted T-stub configurations. The proposed approach accounts for nonlinear behavior, thereby reflecting realistic structural responses. To enhance the simulation efficiency and reduce the computational time without significantly compromising accuracy, the study introduces a simplified modeling methodology. The effectiveness of the approach is demonstrated through the development and experimental validation of a selected T-stub connection. Furthermore, a parameter sensitivity analysis is conducted to showcase the range of possible outcomes, emphasizing the potential for optimization. Finally, the proposed connections were optimized using GA, highlighting the benefits of structural optimization in achieving efficient and precise designs for steel connections.https://www.mdpi.com/2412-3811/10/1/8T-stub steel connectionfinite element methodnonlinear analysisgenetic algorithm |
| spellingShingle | Péter Grubits Tamás Balogh Majid Movahedi Rad Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm Infrastructures T-stub steel connection finite element method nonlinear analysis genetic algorithm |
| title | Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm |
| title_full | Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm |
| title_fullStr | Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm |
| title_full_unstemmed | Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm |
| title_short | Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm |
| title_sort | optimization of bolted steel t stub connection based on nonlinear finite element analysis using genetic algorithm |
| topic | T-stub steel connection finite element method nonlinear analysis genetic algorithm |
| url | https://www.mdpi.com/2412-3811/10/1/8 |
| work_keys_str_mv | AT petergrubits optimizationofboltedsteeltstubconnectionbasedonnonlinearfiniteelementanalysisusinggeneticalgorithm AT tamasbalogh optimizationofboltedsteeltstubconnectionbasedonnonlinearfiniteelementanalysisusinggeneticalgorithm AT majidmovahedirad optimizationofboltedsteeltstubconnectionbasedonnonlinearfiniteelementanalysisusinggeneticalgorithm |