2022/10/03 by Jichao Yin, Hu Wang, Yin, Jichao +5
Computer Science · Engineering · #Advanced Multi-Objective Optimization Algorithms #Computational Engineering #FOS: Computer and information sciences #Finance #Metaheuristic Optimization Algorithms Research #Topology Optimization in Engineering #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2210.00947
openalex publication_date 2022/10/03 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
To improve the computational efficiency of heat transfer topology optimization, a Multigrid Assisted Reanalysis (MGAR) method is proposed in this study. The MGAR not only significantly improves the computational efficiency, but also relieves the hardware burden, and thus can efficiently solve large-scale heat transfer topology optimization problems. In addition, a projection-based post-processing strategy is also proposed and integrated with a continuous density filtering strategy to successfully obtain smooth boundary while eliminating some small-sized features. Several 2D and 3D numerical examples demonstrate that the computational efficiency of the MGAR is close to or even higher than that of the MGCG with almost identical optimization results, moreover, the efficiency improvement in the 3D scenario is superior than that of the 2D scenario, which reveals the excellent potential of the MGAR to save computational cost for large-scale problems.