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Optimization of variable stiffness composites in Automated Fiber Placement Process Using Evolutionary Algorithms

机译:进化算法自动化光纤放置过程中可变刚度复合材料的优化

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Stiffness variety in composite parts is performed by local improvement in directions which are more favorable to carry loads in Automated Fiber Placement (AFP) technology. An approach to find the optimum position and the best length of layup dropping in AFP technology is introduced. Since, the objectives are minimum weight and maximum stiffness, problem is considered as a multi-objective optimization. Fiber failure, matrix cracking, and onset of delamination take into account as the constraints for objective function. A comparative study is introduced to evaluate the performance of Genetic algorithm and Firefly algorithm in finding the global optimum result.
机译:复合部件中的刚度变化是通过局部改进来执行的,方向上更有利地携带自动纤维放置(AFP)技术中的负载。介绍了一种方法,以找到最佳位置和AFP技术中掉线掉铺设的最佳掉线。由于目标是最小重量和最大刚度,问题被认为是多目标优化。纤维失败,矩阵开裂和分层的开始考虑到目标函数的约束。介绍了比较研究以评估遗传算法和萤火虫算法在找到全局最优结果时的性能。

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