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

QUAN Song; HUANG Lihua

doi:10.13206/j.gjgS22032502

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

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

doi: 10.13206/j.gjgS22032502

QUAN Song,
HUANG Lihua^,

Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China

Received Date: 2022-03-25
Available Online: 2023-04-20

Abstract

Abstract

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.
- cold-formed thin-walled channel steel column,
- buckling load,
- section optimization,
- GEP algorithm,
- PSO algorithm

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References(31)

References

[1]	陈绍蕃.卷边槽钢的局部相关屈曲和畸变屈曲[J].建筑结构学报,2002,23(1):27-31.
[2]	何子奇,周绪红,刘占科,等.冷弯薄壁卷边槽钢轴压构件畸变与局部相关屈曲试验研究[J].建筑结构学报,2013,34(11):98-108.
[3]	何保康,蒋路,姚行友,等.高强冷弯薄壁型钢卷边槽形截面轴压柱畸变屈曲试验研究[J].建筑结构学报,2006,27(3):10-17.
[4]	李元齐,王树坤,沈祖炎,等.高强冷弯薄壁型钢卷边槽形截面轴压构件试验研究及承载力分析[J].建筑结构学报,2010,31(11):17-25.
[5]	Dinis P B,Young B,Camotim D.Local-distortional interaction in cold-formed steel rack-section columns[J].Thin-Walled Structures,2014,81:185-194.
[6]	Tohidi S,Sharifi Y.Neural networks for inelastic distortional buckling capacity assessment of steel I-beams[J].Thin-Walled Structures,2015,94:359-371.
[7]	Mallela U K,Upadhyay A.Buckling load prediction of laminated composite stiffened panels subjected to in-plane shear using artificial neural networks[J].Thin-Walled Structures,2016,102:158-164.
[8]	Tran V,Kim S.Efficiency of three advanced data-driven models for predicting axial compression capacity of CFDST columns[J].Thin-Walled Structures,2020,152.DOI: 10.1016/j.tws.2020.106744.
[9]	Adeli H,Karim A.Neural network model for optimization of cold-formed steel beams[J].Journal of Structural Engineering,1997,123 (11):1535-1543.
[10]	Ye J,Hajirasouliha I,Becque J,et al.Optimum design of cold-formed steel beams using Particle Swarm Optimization Method[J].Journal of Constructional Steel Research,2016,122:80-93.
[11]	王永标.冷弯薄壁型钢多卷边组合柱受力性能研究[D].南京:东南大学,2018.
[12]	邓露,钟玉婷,杨远亮,等.冷弯薄壁型钢受弯构件承载力与延性优化研究[J].工程力学,2021,38(4):93-101.
[13]	Ye J,Becque J,Hajirasouliha I,et al.Development of optimum cold-formed steel sections for maximum energy dissipation in uniaxial bending[J].Engineering Structures,2018,161:55-67.
[14]	Duoc T P,Seyed M M,Iman H,et al.Design and optimization of cold-formed steel sections in bolted moment connections considering bimoment[J].Journal of Structural Engineering,2020,146(8).DOI: 10.1061/(ASCE)ST.1943-541X.0002715.
[15]	Kwon Y B,Kim B S,Hancock G J.Compression tests of high strength cold-formed steel channels with buckling interaction[J].Journal of Constructional Steel Research,2009,65(2):278-289.
[16]	Young B,Silvestre N,Camotim D.Cold-formed steel lipped channel columns influenced by local- distortional interaction:strength and DSM design[J].Journal of Structural Engineering,2012,139(6):1059-1074.
[17]	Loughlan J,Yidris N,Jones K.The failure of thin-walled lipped channel compression members due to coupled local-distortional interactions and material yielding[J].Thin-Walled Structures,2012,61:14-21.
[18]	Chen M,Young B,Martins A D,et al.Experimental investigation on cold-formed steel stiffened lipped channel columns undergoing local-distortional interaction[J].Thin-Walled Structures,2020,150.DOI: 10.1016/j.tws.2020.106682.
[19]	杨文斌.高强冷弯薄壁卷边槽钢轴心受压稳定性能研究[D].大连:大连理工大学,2020.
[20]	史婷伟.冷弯薄壁平槽钢屈曲分析[D].大连:大连理工大学,2019.
[21]	Young B,Rasmussen K J R.Tests of fixed-ended plain channel columns[J].Journal of Structural Engineering,1998,124(2):131-139.
[22]	Young B,Rasmussen K J R.Design of lipped channel columns[J].Journal of Structural Engineering,1998,124(2):140-148.
[23]	陈明.腹板加强型冷弯薄壁卷边槽钢柱畸变屈曲理论分析与试验研究[D].兰州:兰州大学,2018.
[24]	何子奇.冷弯薄壁型钢轴压构件畸变及与局部相关的失稳机理和设计理论[D].兰州:兰州大学,2014.
[25]	He Z,Zhou X,Liu Z,et al.Post-buckling behavior and DSM design of web-stiffened lipped channel columns with distortional and local mode interaction[J].Thin-Walled Structures,2014,84:189-203.
[26]	Manikandan P,Sukumar S,Kannan K.Distortional buckling behavior of intermediate cold-formed steel lipped channel section with various web stiffeners under compression[J].International Journal of Advanced Structural Engineering,2018,10:189-198.
[27]	康磊.冷弯薄壁卷边带肋槽钢轴压局部与畸变耦合屈曲分析[D].大连:大连理工大学,2021.
[28]	CEN.Eurocode 3 - Design of steel structures-part 1-3:general rules-supplementary rules for cold-formed members and sheeting:EN 1993-1-3:2006[S].Brussels:European Committee for Standardization,2005.
[29]	Bonada J,Casafont M,Roure F,et al.Selection of the initial geometrical imperfection in nonlinear FE analysis of cold-formed steel rack columns[J].Thin-Walled Structures,2012,51:99-111.
[30]	Deng L,Li J,Yang Y,et al.Imperfection sensitivity analysis and DSM design of web-stiffened lipped channel columns experiencing local-distortional interaction[J].Thin-Walled Structures,2020,152.DOI: 10.1016/j.tws.2020.106699.
[31]	Ferreira C.Gene expression programming[M].Portugal:Angora do Heroismo,2002.