A novel maximum volume sampling model for reliability analysis


Meng Z., Pang Y., Wu Z., Ren S., YILDIZ A. R.

APPLIED MATHEMATICAL MODELLING, vol.102, pp.797-810, 2022 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 102
  • Publication Date: 2022
  • Doi Number: 10.1016/j.apm.2021.10.025
  • Journal Name: APPLIED MATHEMATICAL MODELLING
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Pollution Abstracts, Sociological abstracts, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.797-810
  • Keywords: Reliability, Optimization, Sampling strategy, Givens transformation, Maximum volume sampling model, SUBSET SIMULATION, PROBABILITY, APPROXIMATE, EFFICIENCY, STABILITY, ACCURACY, MOMENTS

Abstract

In this study, a maximum volume sampling model is proposed to improve the accuracy and efficiency of reliability computation. An ellipsoid is constructed with the maximum volume approach in a safe domain, and a new maximum volume optimization method is proposed. The sampling model only computes the samples outside the ellipsoid, which considerably enhances computational efficiency. Furthermore, the uniform sampling strategy and Givens transformation are adopted to efficiently solve the maximum volume optimization model. A series system example, a three-dimensional rock slope example, and an arch bridge example are tested to verify the validity of the proposed maximum volume sampling model. The results indicate that the maximum volume sampling model displays high accuracy and efficiency. (c) 2021 Elsevier Inc. All rights reserved.