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针对大变形非线性结构拓扑优化问题,提出了基于混合细胞自动机(HCA,Hybrid CellularAutomata)多空间域连续体结构拓扑优化方法;采用密度法,建立了单元相对密度表示的材料弹-塑性模型;以单元相对密度和应变能作为细胞自动机(CA,Cellular Automata)的状态信息,利用CA局部控制规则,修改相对密度,迭代实现各设计空间域应变能均匀分布;设计了多空间域拓扑优化HCA算法,采取多个对象同时耦合优化迭代,各自收敛策略,解决了多空间域优化迭代算法收敛稳定性问题;最后,以汽车保险杆结构横梁和支撑等两个设计空间为例,施加大变形动态载荷作用,对提出的多空间结构优化算法进行了验证,优化后结构有效地降低了碰撞作用力峰值达54%,提高了结构安全性.
In order to solve the topological optimization problem of large deformation nonlinear structures, a topology optimization method based on hybrid cellular automata (HCA) is proposed. Based on the density method, a material-plastic model of material relative density is established. The relative density and strain energy of cell were used as the state information of Cellular Automata (CA), and the relative density was modified by using the local control rules of CA. The uniform distribution of strain energy in each design space was iterated. The multi-space domain topological optimization (HCA) Algorithm to solve the problem of convergence stability of multi-space domain optimization iterative algorithm by taking multiple objects simultaneously coupled and optimized iteration and their respective convergence strategies. Finally, taking two design spaces such as beams and supports of bumper structure as an example, large deformation dynamic The proposed load-space optimization algorithm is validated. The optimized structure effectively reduces the peak value of impact force by 54% and improves the structural safety.