结构工程
粒子群优化
有限元法
屈曲
横截面(物理)
冷弯型钢
高强度钢
章节(排版)
非线性系统
工程类
材料科学
计算机科学
算法
物理
量子力学
操作系统
作者
Lingfeng Yin,Tianyang Deng,Yu Niu,Zhanjie Li
出处
期刊:Buildings
[Multidisciplinary Digital Publishing Institute]
日期:2022-12-01
卷期号:12 (12): 2101-2101
被引量:3
标识
DOI:10.3390/buildings12122101
摘要
The high yielding strength of advanced high-strength steel (AHSS) provides great opportunities for cold-formed steel (CFS) members with much higher load-carrying capability. However, if manufactured into the traditional cross-section shapes, such as C and Z, the material advantage cannot be fully exploited due to the cross-section instabilities. The purpose of this study was to establish a shape optimization method for cold-formed sections with AHSS and explore the potentially material efficiency that AHSS could provide to these sections in terms of their axial strength. In this study, the insights provided from the elastic buckling analysis and nonlinear finite element (FE) simulations of a set of traditional CFS sections were employed to determine the appropriate section size and length for optimization. Then, the optimization method was established using the particle swarm optimization (PSO) algorithm with the integration of computational analysis through CUFSM and the design approach (i.e., the direct strength method, DSM). The objective function is the maximum axial strength of the CFS sections manufactured with AHSS using the same amount of material (i.e., the same cross-section area). Finally, the optimal sections were simulated and verified by FE analysis, and the characteristics of the optimal cross-sections were analyzed. Overall, the optimization method in this paper achieved good optimization results with greatly improved axial strength capacity from the optimal sections.
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