A novel preconditioned conjugate gradient multigrid method for multi-material topology optimization

In recent years, topology optimization has been developed sufficiently and many researchers have concentrated on enhancing to computationally numerical algorithms for computational effectiveness of this method. Along with the development of topology optimization, High Performance Computing (HPC) was marked by a strong dynamic mechanism with a continuous appearance and disappearance of manufacturers, systems, and architectures. Preconditioned conjugate gradient multigrid method (pCGMG) is the most popular in HPC due to its advantage in very large-scale problems. The idea which applies high performance computing to reduce time of running in multi-material topology optimization (MTO) problems with computational time burdens is newly proposed in this article. In multi-material topology optimization procedures, pCGMG is applied for solving linear equation arising from discretization of differential equations. pCGMG is based on mesh size, and then it is powerful to larger scale problems. For the large scale linear static system, minimal compliance-based design is evaluated in this study. This study contributes to a high-performance computing that pCGMG is integrated to an MTO problem, and numerical examples of pCGMG are executed to compare with optimization results in terms of iteration and time-running of different mesh sizes of square wall structure.
Comment: 20 pages