To read this content please select one of the options below:

Improvement of topology optimization method based on level set function in magnetic field problem

Yoshifumi Okamoto (Department of Electrical and Electronic Engineering, Hosei University, Koganei, Japan)
Hiroshi Masuda (Department of Electrical and Electronic Engineering, Hosei University, Koganei, Japan)
Yutaro Kanda (Department of Electrical and Electronic Engineering, Hosei University, Koganei, Japan)
Reona Hoshino (Department of Electrical Engineering and Bioscience, Waseda University, Tokyo, Japan)
Shinji Wakao (Department of Electrical Engineering and Bioscience, Waseda University, Tokyo, Japan)

Abstract

Purpose

The purpose of this paper is the improvement of topology optimization. The scope of the paper is focused on the speedup of optimization.

Design/methodology/approach

To achieve the speedup, the method of moving asymptotes (MMA) with constrained condition of level set function is applied instead of solving the Hamilton–Jacobi equation.

Findings

The acceleration of convergence of objective function is drastically improved by the implementation of MMA.

Originality/value

Normally, the level set method is solved through the Hamilton–Jacobi equation. However, the possibility of introducing mathematical programming is clear by the constrained condition. Furthermore, the proposed method is suitable for efficiently solving the topology optimization problem in the magnetic field system.

Keywords

Acknowledgements

This work was supported by the JSPS (Japan Society for the Promotion of Science) Grant-in-Aid for Scientific Research (C) Grant Number 16K06240.

Citation

Okamoto, Y., Masuda, H., Kanda, Y., Hoshino, R. and Wakao, S. (2018), "Improvement of topology optimization method based on level set function in magnetic field problem", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 37 No. 2, pp. 630-644. https://doi.org/10.1108/COMPEL-12-2016-0528

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

Related articles