Efficient imprecise reliability analysis using the Augmented Space Integral

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Xiukai Yuan
  • Matthias G.R. Faes
  • Shaolong Liu
  • Marcos A. Valdebenito
  • Michael Beer

Externe Organisationen

  • The University of Liverpool
  • Tongji University
  • Xiamen University
  • KU Leuven
  • Universidad Adolfo Ibanez
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer107477
FachzeitschriftReliability engineering & system safety
Jahrgang210
Frühes Online-Datum22 Feb. 2021
PublikationsstatusVeröffentlicht - Juni 2021

Abstract

This paper presents an efficient approach to compute the bounds on the reliability of a structure subjected to uncertain parameters described by means of imprecise probabilities. These imprecise probabilities arise from epistemic uncertainty in the definition of the hyper-parameters of a set of random variables that describe aleatory uncertainty in some of the structure's properties. Typically, such calculation involves the solution of a so-called double-loop problem, where a crisp reliability problem is repeatedly solved to determine which realization of the epistemic uncertainties yields the worst or best case with respect to structural safety. The approach in this paper aims at decoupling this double loop by virtue of the Augmented Space Integral. The core idea of the method is to infer a functional relationship between the epistemically uncertain hyper-parameters and the probability of failure. Then, this functional relationship can be used to determine the best and worst case behavior with respect to the probability of failure. Three case studies are included to illustrate the effectiveness and efficiency of the developed methods.

ASJC Scopus Sachgebiete

Zitieren

Efficient imprecise reliability analysis using the Augmented Space Integral. / Yuan, Xiukai; Faes, Matthias G.R.; Liu, Shaolong et al.
in: Reliability engineering & system safety, Jahrgang 210, 107477, 06.2021.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Yuan X, Faes MGR, Liu S, Valdebenito MA, Beer M. Efficient imprecise reliability analysis using the Augmented Space Integral. Reliability engineering & system safety. 2021 Jun;210:107477. Epub 2021 Feb 22. doi: 10.1016/j.ress.2021.107477
Yuan, Xiukai ; Faes, Matthias G.R. ; Liu, Shaolong et al. / Efficient imprecise reliability analysis using the Augmented Space Integral. in: Reliability engineering & system safety. 2021 ; Jahrgang 210.
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note = "Funding Information: Xiukai Yuan would like to acknowledge financial support from NSAF (Grant No. U1530122), the Aeronautical Science Foundation of China (Grant No. ASFC-20170968002). Matthias Faes gratefully acknowledges the financial support of the Research Foundation Flanders (FWO) under grant number 12P3519N, as well as the Alexander von Humboldt foundation. Marcos Valdebenito acknowledges the support of ANID (National Agency for Research and Development, Chile ) under its program FONDECYT, grant number 1180271.",
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AU - Valdebenito, Marcos A.

AU - Beer, Michael

N1 - Funding Information: Xiukai Yuan would like to acknowledge financial support from NSAF (Grant No. U1530122), the Aeronautical Science Foundation of China (Grant No. ASFC-20170968002). Matthias Faes gratefully acknowledges the financial support of the Research Foundation Flanders (FWO) under grant number 12P3519N, as well as the Alexander von Humboldt foundation. Marcos Valdebenito acknowledges the support of ANID (National Agency for Research and Development, Chile ) under its program FONDECYT, grant number 1180271.

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