Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 107477 |
Fachzeitschrift | Reliability engineering & system safety |
Jahrgang | 210 |
Frühes Online-Datum | 22 Feb. 2021 |
Publikationsstatus | Veröffentlicht - 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
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: Reliability engineering & system safety, Jahrgang 210, 107477, 06.2021.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Efficient imprecise reliability analysis using the Augmented Space Integral
AU - Yuan, Xiukai
AU - Faes, Matthias G.R.
AU - Liu, Shaolong
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.
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
KW - Augmented space
KW - Imprecise reliability analysis
KW - Interval variable
KW - Simulation-based method
UR - http://www.scopus.com/inward/record.url?scp=85101722587&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2021.107477
DO - 10.1016/j.ress.2021.107477
M3 - Article
AN - SCOPUS:85101722587
VL - 210
JO - Reliability engineering & system safety
JF - Reliability engineering & system safety
SN - 0951-8320
M1 - 107477
ER -