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Application of genetic algorithm for optimum design of bolted composite lap joints

机译：遗传算法在螺栓复合搭接优化设计中的应用

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The genetic algorithm (GA), a powerful optimization technique for multiple extrema functions in multidimensional search spaces, is applied in conjunction with stress analysis to achieve optimum designs of bolted composite lap joints. The objective of the optimization is to ensure the highest strength of the joint. In this study, the laminate thickness, laminate lay-up, bolt location, bolt flexibility, and bolt size are considered as design variables. The contact stresses (bolt loads) are determined by a combined complex potential and variational formulation. In this formulation, the equilibrium equations are satisfied exactly and the boundary conditions are enforced by minimizing the total potential. The contact stresses as well as the contact region are determined through an iterative procedure as part of a solution method that accounts for the effects of finite geometry and by-pass loading. The fitness function for the GA optimization is based on the average stress failure criterion for predicting net-section, shear-out, and bearing failure modes in bolted lap joints.
机译：遗传算法（GA）是针对多维搜索空间中多个极值函数的强大优化技术，与应力分析结合使用以实现螺栓复合搭接的最优设计。优化的目的是确保接头的最高强度。在这项研究中，层压板的厚度，层压板的层叠，螺栓的位置，螺栓的柔韧性和螺栓的尺寸均被视为设计变量。接触应力（螺栓载荷）由复杂的电势和变化的公式确定。在该公式中，精确地满足了平衡方程，并通过使总电势最小化来实施边界条件。作为解决方法的一部分，通过迭代过程确定接触应力以及接触区域，该解决方法考虑了有限的几何形状和旁路载荷的影响。 GA优化的适应度函数基于平均应力破坏准则，用于预测螺栓搭接接头的净截面，剪力和轴承破坏模式。

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