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 journalArticle

    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

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

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