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Optimum design of cold-formed steel columns by using micro genetic algorithms

机译:基于微观遗传算法的冷弯钢柱优化设计

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Cold-formed steel members such as beams and columns have the great flexibility of cross-sectional profiles and sizes available to structural steel designers. However, this flexibility makes the selection of the most economical section difficult for a particular situation. In this study, micro genetic algorithm (MGA) is used to find an optimum cross section of cold-formed steel channel and lipped channel columns under axial compression. Flexural, torsional and torsional-flexural buckling of columns and flat-width-to-thickness ratio of web, flange and lip are considered as constraints. The design curves are generated for optimum values of the thickness, the web flat-depth-to-thickness ratio, the flange flat-width-to-thickness ratio for columns. As numerical results, the optimum design curves are presented for various load level and column lengths.
机译:诸如梁和柱之类的冷弯型钢构件具有极大的灵活性,可用于结构钢设计人员的截面轮廓和尺寸。但是,这种灵活性使得在特定情况下很难选择最经济的部分。在这项研究中,使用微遗传算法(MGA)来寻找轴向压缩下冷弯型钢槽钢和唇形槽钢柱的最佳横截面。柱的挠曲,扭转和扭转挠曲屈曲以及腹板,翼缘和唇缘的扁平宽度与厚度之比被视为约束条件。设计曲线的生成是为了获得最佳的厚度,柱子的腹板平坦深度与厚度比,法兰平坦宽度与厚度比的值。作为数值结果,给出了各种载荷水平和柱长的最佳设计曲线。

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