Hybrid reliability-based multidisciplinary design optimization with random and interval variables

Fan Yang, Zhufeng Yue, Lei Li, Dong Guan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

This article presents a procedure for reliability-based multidisciplinary design optimization with both random and interval variables. The sign of performance functions is predicted by the Kriging model which is constructed by the so-called learning function in the region of interest. The Monte Carlo simulation with the Kriging model is performed to evaluate the failure probability. The sample methods for the random variables, interval variables, and design variables are discussed in detail. The multidisciplinary feasible and collaborative optimization architectures are provided with the proposed method. The method is demonstrated with three examples.

Original languageEnglish
Pages (from-to)52-64
Number of pages13
JournalProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Volume232
Issue number1
DOIs
StatePublished - 1 Feb 2018

Keywords

  • collaborative optimization
  • hybrid reliability
  • Kriging model
  • multidisciplinary feasible
  • Reliability-based multidisciplinary design optimization

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