Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space. Issue 3 (2014) - ,; ,; ,; ,
Abstract : Purpose – The purpose of this paper is to improve the multistep algorithm using evolutionary algorithm (EA) for the topology optimization of magnetostatic shielding, and the paper reveals the effectiveness of methodology by comparison with conventional optimization method. Furthermore, the design target is to obtain the novel shape of magnetostatic shielding.Design/methodology/approach – The EAs based on random search allow engineers to define general‐purpose objects with various constraint conditions; however, many iterations are required in the FEA for the evaluation of the objective function, and it is difficult to realize a practical solution without island and void distribution. Then, the authors proposed the multistep algorithm with design space restriction, and improved the multistep algorithm in order to get better solution than the previous one.Findings – The variant model of optimized topology derived from improved multistep algorithm is defined to clarify the effectiveness of the optimized topology. The upper curvature of the inner shielding contributed to the reduction of magnetic flux density in the target domain.Research limitations/implications – Because the converged topology has many pixel element unevenness, the special smoother to remove the unevenness will play an important role for the realization of practical magnetostatic shielding.Practical implications – The optimized topology will give us useful detailed structure of magnetostatic shielding.Originality/value – First, while the conventional algorithm could not find the reasonable shape, the improved multistep optimization can capture the reasonable shape. Second, An additional search is attached to the multistep optimization procedure. It is shown that the performance of improved multistep algorithm is better than that of conventional algorithm. Acknowledgements : This work was supported by JSPS (Japan Society for the Promotion of Science) Grant‐in‐Aid for Young Scientists (B) Grant Number 25820099.