摘要
由于具备高的比强度、比刚度,利用连续纤维增强复合材料代替传统金属材料以实现结构轻量化正受到设计者们的广泛关注.然而,结构的复杂性给复合材料的铺层设计与优化带来了很大的挑战.针对航空用复合材料铺层设计约束多的问题,通过逐步构建设计变量准确表达结构的铺层信息.基于经典遗传算法框架,结合各设计变量特点,定义了铺层优化算法中的遗传算子,通过引入“修复”策略保证了每一代解都能满足设计约束,分布在可行域区间内.最后利用精英保留策略提高了算法的局部寻优能力,可以降低复杂复合材料结构铺层设计的计算成本.通过解决经典benchmark问题并与已有优化结果的比较,验证了前述铺层优化算法的全局、局部寻优能力,为工程实际中的复合材料铺层设计优化提供了理论支撑.
Due to the high specific strength and stiffness,the use of continuous fiber reinforced composites instead of traditional metal materials to achieve structural lightweight has been widely considered by designers.However,the structural complexity brings great challenges to the design and optimization of composite lamination.Aimed at the problem of multiple constraints in the design of aviation composite laminates,the ply information of the structure was accurately expressed with gradually constructed design variables.Based on the classical genetic algorithm framework and the characteristics of all design variables,the genetic operators in the lamination optimization algorithm were defined,and the repair strategy was introduced to ensure that each generation of solutions could satisfy the design constraints and be distributed in the feasible region.Finally,the elite reservation strategy was used to improve the local optimization ability of the algorithm,which can reduce the computation cost of the lamination design of complex composite structures.Through the resolution of the classical benchmark problem and the comparison with the existing optimization results,the global and local optimization ability of the proposed lamination optimization algorithm was verified.The work provides theoretical supports for the optimization of composite lamination design in engineering practice.
作者
杜晨
彭雄奇
DU Chen;PENG Xiongqi(School of Materials Science and Engineering,Shanghai Jiao Tong University,Shanghai 200030,P.R.China)
出处
《应用数学和力学》
CSCD
北大核心
2022年第12期1313-1323,共11页
Applied Mathematics and Mechanics
基金
国家自然科学基金(U20A20288,11972225)。
关键词
连续纤维增强复合材料
铺层设计优化
遗传算法
“修复”策略
寻优能力
continuous fiber reinforced composites
layer design optimization
genetic algorithm
repair strategy
optimization ability
