TY - JOUR

T1 - Failure Probability Estimation of a Class of Series Systems by Multidomain Line Sampling

AU - Valdebenito, Marcos A.

AU - Wei, Pengfei

AU - Song, Jingwen

AU - Beer, Michael

AU - Broggi, Matteo

N1 - Funding Information: This research is partially supported by ANID (National Agency for Research and Development, Chile) under its program FONDECYT , grant number 1180271 and the National Natural Science Foundation of China (NSFC) under grant number NSFC 51905430 . The first author developed part of this work during a research stay at the Institute for Risk and Reliability (IRZ) of the Leibniz Universität Hannover, Germany. Both the first and second authors conducted this research under the auspice of the Alexander von Humboldt Foundation. This support is gratefully acknowledged by the authors.

PY - 2021/9

Y1 - 2021/9

N2 - This contribution proposes an approach for the assessment of the failure probability associated with a particular class of series systems. The type of systems considered involves components whose response is linear with respect to a number of Gaussian random variables. Component failure occurs whenever this response exceeds prescribed deterministic thresholds. We propose multidomain Line Sampling as an extension of the classical Line Sampling to work with a large number of components at once. By taking advantage of the linearity of the performance functions involved, multidomain Line Sampling explores the interactions that occur between failure domains associated with individual components in order to produce an estimate of the failure probability. The performance and effectiveness of multidomain Line Sampling is illustrated by means of two test problems and an application example, indicating that this technique is amenable for treating problems comprising both a large number of random variables and a large number of components.

AB - This contribution proposes an approach for the assessment of the failure probability associated with a particular class of series systems. The type of systems considered involves components whose response is linear with respect to a number of Gaussian random variables. Component failure occurs whenever this response exceeds prescribed deterministic thresholds. We propose multidomain Line Sampling as an extension of the classical Line Sampling to work with a large number of components at once. By taking advantage of the linearity of the performance functions involved, multidomain Line Sampling explores the interactions that occur between failure domains associated with individual components in order to produce an estimate of the failure probability. The performance and effectiveness of multidomain Line Sampling is illustrated by means of two test problems and an application example, indicating that this technique is amenable for treating problems comprising both a large number of random variables and a large number of components.

KW - Failure probability

KW - Line sampling

KW - Linear performance function

KW - Multidomain

KW - Series system

UR - http://www.scopus.com/inward/record.url?scp=85104334307&partnerID=8YFLogxK

U2 - 10.1016/j.ress.2021.107673

DO - 10.1016/j.ress.2021.107673

M3 - Article

VL - 213

JO - Reliability Engineering and System Safety

JF - Reliability Engineering and System Safety

SN - 0951-8320

M1 - 107673

ER -