作　　者： ; ; ; ;

机构地区： 南京航空航天大学能源与动力学院

出　　处： 《固体力学学报》 2009年第4期416-423,共8页

摘　　要： 利用高精度通用单胞模型将复合材料的细观拓扑结构与宏观力学性能结合起来,采用遗传算法对复合材料的细观结构进行优化,发展了基于遗传算法的复合材料细观结构拓扑优化设计方法.以材料的宏观力学性能为优化目标,从随机的初始细观结构出发,对复合材料纤维体积百分比进行约束,经过迭代获得满足设计要求的代表性体积单元.在优化过程中,对遗传算法的交叉过程作了较大的改进,实现了复合材料细观拓扑结构的任意变化,提高了对可行域的搜索效率.分别以极限剪切模量和泊松比为优化目标,验证了所提出优化方法的正确性和有效性. In order to develop a method of composite microstructure topological optimization, the topological microstructure and mechanical properties are combined with the High-fidelity Generalized Method of Cell （HFGMC）, and genetic algorithm is used to optimize the microstructure of composite. The object of optimization is mechanical properties of composite. To this end, the present algorithm starts with random topological microstructures, and then an iterative algorithm is designed to generate the Representative Volume Element （RVE） satisfying the design requirements with constrained fiber volume fraction. During the optimization procedure, great improvement of crossbreed of genetic algorithm achieves the random transformation of the topological microstructure of composite, and also improves the search efficiency in the feasible domain. In order to verify the validity of the developed method, the extremal shear module and Poisson ratio are considered as objective of optimization respectively.

关 键 词： 复合材料 细观结构 拓扑优化 遗传算法 剪切模量 拉胀性能

领　　域： [建筑科学] [一般工业技术]