Structural design optimization based on hybrid time-variant reliability measure under non-probabilistic convex uncertainties

Lei Wang*, Yujia Ma, Yaowen Yang, Xiaojun Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

Structural safety assessment issue, considering the influence of uncertain factors, is widely concerned currently. However, uncertain parameters present time-variant characteristics during the entire structural design procedure. Considering materials aging, loads varying and damage accumulation, the current reliability-based design optimization (RBDO) strategy that combines the static/time-invariant assumption with the random theory will be inapplicable when tackling with the optimal design issues for lifecycle mechanical problems. In light of this, a new study on non-probabilistic time-dependent reliability assessment and design under time-variant and time-invariant convex mixed variables is investigated in this paper. The hybrid reliability measure is first given by the first-passage methodology, and the solution aspects should depend on the regulation treatment and the convex theorem. To guarantee the rationality and efficiency of the optimization task, the improved GA algorithm is involved. Two numerical examples are discussed to demonstrate the validity and usage of the presented methodology.

Original languageEnglish
Pages (from-to)330-354
Number of pages25
JournalApplied Mathematical Modelling
Volume69
DOIs
Publication statusPublished - May 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Inc.

ASJC Scopus Subject Areas

  • Modelling and Simulation
  • Applied Mathematics

Keywords

  • Convex mixed variables
  • Non-probabilistic time-variant hybrid reliability optimization
  • The first-passage method
  • The improved GA algorithm

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