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A mixed finite element and improved genetic algorithm method for maximizing buckling load of stiffened laminated composite plates

机译:最大化加筋层压板屈曲载荷的混合有限元和改进遗传算法

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摘要

As a first attempt, finite element (FE), genetic algorithm (GA) and particle swarm optimization (PSO) methods are mixed to maximize buckling load of stiffened laminated composite plate via finding optimum fibers orientation of the plate. The FE method is used to solve the higher-order shear deformation based equations of the plate. To improve the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence and applicability of the proposed approach are shown. Effects of the dimensions of the plate, the cross section shapes of the stiffener(s), number of layers of the plate and boundary conditions on the optimum results are investigated. (C) 2017 Elsevier Masson SAS. All rights reserved.
机译:作为首次尝试,将有限元(FE),遗传算法(GA)和粒子群优化(PSO)方法混合在一起,以通过找到板的最佳纤维方向来最大化加硬层压复合板的屈曲载荷。有限元方法用于求解基于板的高阶剪切变形方程。为了提高遗传算法解决该问题的性能,增加了粒子群优化技术作为遗传算法的算子。显示了该方法的准确性,收敛性和适用性。研究了板的尺寸,加劲肋的横截面形状,板的层数和边界条件对最佳结果的影响。 (C)2017 Elsevier Masson SAS。版权所有。

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