Iterative reanalysis approximation‐assisted moving morphable component‐based topology optimization method

An Iterative Reanalysis Approximation- (IRA) assisted Moving Morphable Components- (MMCs) based topology optimization is developed (IRA-MMC) in this study. Compared with other classical topology optimization methods, Finite Element-based solver is replaced with the suggested IRA. In this way, the expensive computational cost can be significantly saved by several nested iterations. In the suggested algorithm, a hybrid optimizer based on Method of Moving Asymptotes approach and Globally Convergent version of Method of Moving Asymptotes is suggested to improve convergence ratio and avoid local optimum. Finally, the proposed approach is evaluated by some classical benchmark problems in topology optimization. The results show significant time saving without compromising accuracy.