Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method
Transmission towers operate in complex engineering environments, such as gravity, strong winds, ice and snow, wire breaking and unbalanced loads. Owing to complicated structural parameters, multiple load cases and multiple constraint conditions, the optimal design plan of the structure is difficult...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2023-06-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/16878132231183764 |
| _version_ | 1797794374742966272 |
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| author | Yinqi Li Songfeng Liang Peng Li Yuanzhi Xu |
| author_facet | Yinqi Li Songfeng Liang Peng Li Yuanzhi Xu |
| author_sort | Yinqi Li |
| collection | DOAJ |
| description | Transmission towers operate in complex engineering environments, such as gravity, strong winds, ice and snow, wire breaking and unbalanced loads. Owing to complicated structural parameters, multiple load cases and multiple constraint conditions, the optimal design plan of the structure is difficult to acquire. Popular intelligent algorithms (Genetic Algorithm, GA; Particle Swarm Optimisation, PSO; and others) need to spend time in structural mechanical computation and search processes. To solve this problem, the commercial FE software ABAQUS was used to build the full parametric analytical and computational sub-procedures (general static, linear buckling and cost computation) for the transmission tower under multiple load cases and constraint conditions. Then, the main algorithm procedure, KSM-GA, was developed based on the GA optimiser and Kriging Surrogate Model (KSM). The KSM-GA could import the design variables (such as cross-section properties and structural dimensions) of the transmission tower into the FE computational sub-procedures and read the results (including stresses, displacements, buckling load and weight). The results show that the KSM-GA can reduce the search time more than 30% compared with the GA, PSO and BO-GP( Bayesian Optimisation with Gaussian Process) while the training precision of the KSM is above 99% accuracy of the FE results. |
| first_indexed | 2024-03-13T03:01:54Z |
| format | Article |
| id | doaj.art-ae9cbd9c224647b1aebfae9bffdb0c1b |
| institution | Directory Open Access Journal |
| issn | 1687-8140 |
| language | English |
| last_indexed | 2024-03-13T03:01:54Z |
| publishDate | 2023-06-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-ae9cbd9c224647b1aebfae9bffdb0c1b2023-06-27T12:03:20ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402023-06-011510.1177/16878132231183764Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA methodYinqi Li0Songfeng Liang1Peng Li2Yuanzhi Xu3Automotive and Transportation Engineering, Shenzhen Polytechnic College, Shenzhen City, ChinaAutomotive and Transportation Engineering, Shenzhen Polytechnic College, Shenzhen City, ChinaAutomotive and Transportation Engineering, Shenzhen Polytechnic College, Shenzhen City, ChinaKunming Yunnei Power Company Limited, Kunming City, ChinaTransmission towers operate in complex engineering environments, such as gravity, strong winds, ice and snow, wire breaking and unbalanced loads. Owing to complicated structural parameters, multiple load cases and multiple constraint conditions, the optimal design plan of the structure is difficult to acquire. Popular intelligent algorithms (Genetic Algorithm, GA; Particle Swarm Optimisation, PSO; and others) need to spend time in structural mechanical computation and search processes. To solve this problem, the commercial FE software ABAQUS was used to build the full parametric analytical and computational sub-procedures (general static, linear buckling and cost computation) for the transmission tower under multiple load cases and constraint conditions. Then, the main algorithm procedure, KSM-GA, was developed based on the GA optimiser and Kriging Surrogate Model (KSM). The KSM-GA could import the design variables (such as cross-section properties and structural dimensions) of the transmission tower into the FE computational sub-procedures and read the results (including stresses, displacements, buckling load and weight). The results show that the KSM-GA can reduce the search time more than 30% compared with the GA, PSO and BO-GP( Bayesian Optimisation with Gaussian Process) while the training precision of the KSM is above 99% accuracy of the FE results.https://doi.org/10.1177/16878132231183764 |
| spellingShingle | Yinqi Li Songfeng Liang Peng Li Yuanzhi Xu Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method Advances in Mechanical Engineering |
| title | Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method |
| title_full | Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method |
| title_fullStr | Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method |
| title_full_unstemmed | Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method |
| title_short | Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method |
| title_sort | optimisation of transmission towers under multiple load cases and constraint conditions with the ksm ga method |
| url | https://doi.org/10.1177/16878132231183764 |
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