Unified reliability analysis method for structures with multi-source uncertainties

Li Xiang Zhang, Xin Jia Meng, Shi Kai Jing, Ji Hong Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

A unified reliability analysis method is presented to handle the problem of multi-source uncertainties with random, fuzzy and interval variables. In the proposed method, a unified reliability analysis model (URAM) is constructed by applying the conditional failure on the basis of the relationship of probability, possibility, and evidence theories. The URAM belongs to a three layers conditional reliability analysis model, where the basic probability assignment assigned to interval variable is placed in the outermost layer of the conditional failure, the possibility measure assigned to fuzzy variable is placed in the middle layer, and the probability measure assigned to random variable is placed in the innermost layer. An algorithm based on the first order reliability method (FORM) and α-cut, which is referred to as FORM-α-URA, is developed to solve the URAM. The feasibility and effectiveness of the presented methodology are demonstrated by a numerical example.

Original languageEnglish
Title of host publication2016 International Conference on Robotics and Automation Engineering, ICRAE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-125
Number of pages7
ISBN (Electronic)9781509040728
DOIs
Publication statusPublished - 8 Nov 2016
Event2016 International Conference on Robotics and Automation Engineering, ICRAE 2016 - Jeju-Do, Korea, Republic of
Duration: 27 Aug 201629 Aug 2016

Publication series

Name2016 International Conference on Robotics and Automation Engineering, ICRAE 2016

Conference

Conference2016 International Conference on Robotics and Automation Engineering, ICRAE 2016
Country/TerritoryKorea, Republic of
CityJeju-Do
Period27/08/1629/08/16

Keywords

  • FORM-α-URA
  • URAM
  • evidence theory
  • multi-source uncertainties
  • reliability analysis

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