Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space

Yoshifumi Okamoto, Yusuke Tominaga, Shinji Wakao, Shuji Sato

    Research output: Contribution to journalArticle

    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.

    Original languageEnglish
    Article number17111506
    Pages (from-to)894-913
    Number of pages20
    JournalCOMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
    Volume33
    Issue number3
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Magnetostatics
    Topology Optimization
    Shape optimization
    Evolutionary algorithms
    Shielding
    Evolutionary Algorithms
    Topology
    Target
    Random Search
    Optimization
    Magnetic flux
    Voids
    Design
    Design Methodology
    Optimization Methods
    Objective function
    Pixel
    Pixels
    Curvature
    Restriction

    Keywords

    • FE method
    • Optimal design
    • Optimization

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Computer Science Applications
    • Computational Theory and Mathematics
    • Applied Mathematics

    Cite this

    @article{d2ff3c39b8084492bf2088ebef5058b1,
    title = "Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space",
    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.",
    keywords = "FE method, Optimal design, Optimization",
    author = "Yoshifumi Okamoto and Yusuke Tominaga and Shinji Wakao and Shuji Sato",
    year = "2014",
    doi = "10.1108/COMPEL-10-2012-0202",
    language = "English",
    volume = "33",
    pages = "894--913",
    journal = "COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering",
    issn = "0332-1649",
    publisher = "Emerald Group Publishing Ltd.",
    number = "3",

    }

    TY - JOUR

    T1 - Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space

    AU - Okamoto, Yoshifumi

    AU - Tominaga, Yusuke

    AU - Wakao, Shinji

    AU - Sato, Shuji

    PY - 2014

    Y1 - 2014

    N2 - 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.

    AB - 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.

    KW - FE method

    KW - Optimal design

    KW - Optimization

    UR - http://www.scopus.com/inward/record.url?scp=84903202985&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84903202985&partnerID=8YFLogxK

    U2 - 10.1108/COMPEL-10-2012-0202

    DO - 10.1108/COMPEL-10-2012-0202

    M3 - Article

    AN - SCOPUS:84903202985

    VL - 33

    SP - 894

    EP - 913

    JO - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

    JF - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

    SN - 0332-1649

    IS - 3

    M1 - 17111506

    ER -