Material-density-based topology optimization with magnetic nonlinearity by means of stabilized sequential linear programming: SLPSTAB

Yoshifumi Okamoto, Yu Matsubayashi, Shinji Wakao, Shuji Sato

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The nonlinear magnetic properties of an iron core should be considered when topology optimization (TO) is applied to a realistic problem. However, a scheme for introduction of the magnetic nonlinearity to material-density-based TO has not been rigorously established. In this paper, TO by using material density with magnetic nonlinearity is proposed. The numerical instability of the sequential linear programming method is a well-known topic. The stabilized sequential linear programming method, which realizes the stabilized convergence characteristics of an objective function, is proposed and investigated in the 3-D design problem of a magnetic circuit.

Original languageEnglish
Article number7093522
JournalIEEE Transactions on Magnetics
Volume51
Issue number3
DOIs
Publication statusPublished - 2015 Mar 1

Keywords

  • Magnetic nonlinearity
  • material-density-based topology optimization (TO)
  • stabilized sequential linear programming (SLPSTAB) method

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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