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Buckling optimization of laminated composite plates using genetic algorithm and generalized pattern search algorithm

机译:遗传算法和广义模式搜索算法的复合材料层板屈曲优化

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摘要

In this paper, genetic algorithm and generalized pattern search algorithm are used for optimal stacking sequence of a composite panel, which is simply supported on four sides and is subject to biaxial in-plane compressive loads. The problem has several global optimum configurations in the vicinity of local optima. The composite plate under consideration is 64-ply laminate made of graphite/epoxy. The laminate is taken to be symmetric and balanced, comprised of two-ply stacks with discrete fiber angles of 02, ± 45, 902 in the laminate sequence. The critical buckling loads are maximized for several combinations of load case and plate aspect ratio, and are compared with published results. Performance of both algorithms is compared in terms of capability of identifying global optima. It is found that genetic algorithm is efficient for problems with global optima.
机译:本文将遗传算法和广义模式搜索算法用于复合板的最佳堆叠顺序,该方法简单地在四个侧面上得到支撑,并且承受双轴面内压缩载荷。该问题在局部最优附近有几个全局最优配置。所考虑的复合板是由石墨/环氧树脂制成的64层层压板。层压板被认为是对称且平衡的,由两层堆叠组成,纤维在层压序列中的离散纤维角度分别为02 ,±45、902 。对于载荷工况和板高宽比的几种组合,临界屈曲载荷被最大化,并与公开的结果进行比较。根据确定全局最优值的能力比较了两种算法的性能。发现遗传算法对于全局最优问题是有效的。

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