論文

査読有り 筆頭著者
2023年3月24日

Smoothing inertial method for worst-case robust topology optimization under load uncertainty

Structural and Multidisciplinary Optimization
  • Akatsuki Nishioka
  • ,
  • Yoshihiro Kanno

66
4
記述言語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s00158-023-03543-7
出版者・発行元
Springer Science and Business Media LLC

Abstract

We consider a worst-case robust topology optimization problem under load uncertainty, which can be formulated as a minimization problem of the maximum eigenvalue of a symmetric matrix. The objective function is nondifferentiable where the multiplicity of maximum eigenvalues occurs. Nondifferentiability often causes some numerical instabilities in an optimization algorithm such as oscillation of the generated sequence and convergence to a non-optimal point. We use a smoothing method to tackle these issues. The proposed method is guaranteed to converge to a point satisfying the first-order optimality condition. In addition, it is a simple first-order optimization method and thus has low computational cost per iteration even in a large-scale problem. In numerical experiments, we show that the proposed method suppresses oscillation and converges faster than other existing methods.

リンク情報
DOI
https://doi.org/10.1007/s00158-023-03543-7
URL
https://link.springer.com/content/pdf/10.1007/s00158-023-03543-7.pdf
URL
https://link.springer.com/article/10.1007/s00158-023-03543-7/fulltext.html
ID情報
  • DOI : 10.1007/s00158-023-03543-7
  • ISSN : 1615-147X
  • eISSN : 1615-1488

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