【摘要】 目前汽车防撞梁主要采用高碳钢或者铝合金材料,但在设计强度与汽车轻量化方面,碳纤维复合材料(CFRP)有着明显的优势,所以对CFRP汽车防撞梁层合板的性能研究十分重要。将考虑层合板铺层的广义海明距离与遗传算法相结合,提出了能够以汽车防撞梁为模型的优化设计新方法。该算法采用自适应的思想,与传统遗传算法不同,每次重组算子保留最优个体,这有效避免了交叉、变异操作对最优解取值的干扰,解决遗传算法过早收敛的现象。更多还原

【Abstract】 Currently,high carbon steel or aluminum alloy is applied for automobile collision-resistant beam,but carbon-fiber reinforced polymer(CFRP) has obvious advantages in design intensity and light weight. Therefore,it is very important to study the performance of CFRP automobile collision-resistant beam laminate. In this paper,with the combination of the laminate layer’s generalized Hamming distance and the genetic algorithm,a new method of optimization design,which can be used as model of automobile collision-resistant beam,is proposed. This algorithm,based on the adaptive principles,is different from traditional genetic algorithm. Each recombination operator keeps the best individual,which effectively avoids the interference of crossover and mutation operations exerted on the optimal solution,and addresses the premature convergence of the genetic algorithm.更多还原