Efficient topology optimization based on the adaptive auxiliary reduced model reanalysis (AARMR) is proposed to improve computational efficiency and scale. In this method, a projection auxiliary reduced model (PARM) is integrated into the combined approximation reduced model (CARM) to reduce the dimension of the model in different aspects. First, the CARM restricts the solution space to avoid large matrix factorization. Second, the PARM is proposed to construct the CARM dynamically to save computational cost. Furthermore, the multi-grid conjugate gradient method is suggested to update PARM adaptively. Finally, several classic numerical examples are tested to show that the proposed method not only significantly improves computational efficiency, but also can solve large-scale problems that are difficult to solve by direct solvers due to the memory limitations.
翻译:根据适应性辅助性减少模型再分析(ARMR),提议根据适应性辅助性减少模型再分析(AARM)实现高效表层优化,以提高计算效率和规模;在这种方法中,将投影辅助性减少模型(PARM)纳入综合近似减少模型(CARM),以在不同方面缩小模型的维度;首先,CARM限制解决方案空间,以避免大型矩阵化;第二,建议PARM动态建造CARM,以节省计算成本;此外,建议多电网共振梯度法以适应性方式更新PARM。最后,对几个典型的数字实例进行了测试,以表明拟议的方法不仅大大提高了计算效率,而且还能够解决由于内存限制直接解决者难以解决的大规模问题。