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Multiobjective Genetic Algorithm optimization of the composite laminates as a satellite structure material for coefficient of thermal expansion and elastic modulus

机译:复合材料层压板作为卫星结构材料的热膨胀系数和弹性模量的多目标遗传算法优化

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This study considers multi-objective optimal design of the fiber reinforced symmetric-balanced laminated composites using genetic algorithms. MATLAB Genetic Algorithm and Direct Search Toolbox is used to obtain Pareto-optimal design for three different model problems. The objectives of the problems are to maximize the Young's moduli and minimize the coefficient of thermal expansion (CTE) simultaneously for 8 and 16 layered carbon/epoxy composites. Simplified micromechanics equations and classical lamination theory are used in order to obtain the fitness functions of the problems. Stress and strain distributions are presented through the thickness of the laminates for the optimized problems under mechanical and thermal loadings.
机译:本研究考虑了采用遗传算法的纤维增强对称平衡层压复合材料的多目标优化设计。 MATLAB遗传算法和直接搜索工具箱用于获得针对三个不同模型问题的帕累托最优设计。这些问题的目的是使8和16层碳/环氧树脂复合材料的杨氏模量最大化,同时使热膨胀系数(CTE)最小化。为了获得问题的适应度函数,使用了简化的微力学方程和经典的层合理论。应力和应变分布是通过层压板的厚度来表示的,以解决机械和热负荷下的优化问题。

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