Simultaneous Optimization of Carbon Fiber Allocation and Orientation by IFM-GA

Kenta Fukui, Ryota Nonami
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Abstract

This paper proposes an individual fitness method genetic algorithm (IFM-GA) for carbon fiber-reinforced plastic (CFRP). The strength of CFRP depends on the carbon fiber allocation and orientation. Waste carbon fiber is generated if this design is inappropriate. Consequently, CFRPs are less cost-effective. It is necessary to optimize the allocation and orientation as design variables to solve this problem. The problem involves combinatorial optimization. The genetic algorithm (GA) is suitable for combinatorial optimization. However, it is difficult to obtain an optimal solution using the GA owing to the large number of combinations. Hence, the IFM-GA is developed in this study. It is a GA-based method with a different fitness calculation. The GA calculates the fitness of each design, whereas the IFM-GA calculates the fitness of each design element. As a result, the IFM-GA yields a higher-stiffness design than the GA. To conclude, the IFM-GA can enable optimum fiber allocation and orientation, whereas the GA cannot.

用IFM-GA同时优化碳纤维的分配和定向
提出了一种适用于碳纤维增强塑料(CFRP)的个体适应度遗传算法(IFM-GA)。CFRP的强度取决于碳纤维的分布和取向。如果这种设计不合适,就会产生废弃的碳纤维。因此,CFRP的成本效益较低。有必要优化分配和方向作为设计变量来解决这个问题。这个问题涉及组合优化。遗传算法(GA)适用于组合优化。然而,由于组合的数量很大,使用遗传算法很难获得最优解。因此,本研究开发了IFM-GA。这是一种基于遗传算法的方法,具有不同的适应度计算。遗传算法计算每个设计的适合度,而IFM-GA计算每个设计元素的适合度。因此,IFM-GA比GA产生了更高的刚度设计。总之,IFM-GA可以实现最佳的纤维分配和定向,而GA不能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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