Volume 37 Issue 12
Dec.  2022
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QUAN Song, HUANG Lihua. Section Optimization of Elastic-Plastic Buckling of Cold-Formed Thin-Walled Lipped Channel Steel Column Based on Machine Learning[J]. STEEL CONSTRUCTION(Chinese & English), 2022, 37(12): 10-17. doi: 10.13206/j.gjgS22032502
Citation: QUAN Song, HUANG Lihua. Section Optimization of Elastic-Plastic Buckling of Cold-Formed Thin-Walled Lipped Channel Steel Column Based on Machine Learning[J]. STEEL CONSTRUCTION(Chinese & English), 2022, 37(12): 10-17. doi: 10.13206/j.gjgS22032502

Section Optimization of Elastic-Plastic Buckling of Cold-Formed Thin-Walled Lipped Channel Steel Column Based on Machine Learning

doi: 10.13206/j.gjgS22032502
  • Received Date: 2022-03-25
    Available Online: 2023-04-20
  • There are many factors that affect the elastic-plastic buckling capacity of cold-formed thin-wall steel lipped channel members. However, the relationship between section form and bearing capacity cannot be accurately expressed analytically. In order to optimize the section form and improve the buckling capacity of channel steel, the gene expression programming(GEP) algorithm and the particle swarm optimization(PSO) algorithm were combined to optimize section form. Through calling ABAQUS by Python programming, the finite element calculation of 15 test components in the literature was carried out in batches. The accuracy of the numerical solution was verified by comparing with the experimental values. A group of components were selected as samples to carry out anti-buckling section optimization. A total of 97 ensembles of sample data including different section sizes and corresponding buckling loads were generated by the batch finite element calculation. The gene expression programming algorithm was used to fit the dataset, and the surrogate model of the objective function of cross-section optimization was constructed. The particle swarm optimization algorithm was used to obtain the optimal section size corresponding to the maximum elastoplastic buckling capacity of cold-formed thin-walled lipped channel steel. Compared with the original specimen, the buckling capacity is increased by 30.4% after section optimization. The results show that the combination of finite element, machine learning and traditional optimization methods can be adopted to effectively optimize the section form of thin-walled channel column.
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