TY - JOUR

T1 - An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load

AU - Yuan, Xiukai

AU - Liu, Shaolong

AU - Faes, Matthias

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 No. 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 No. 1180271.

PY - 2021/10

Y1 - 2021/10

N2 - Structural performance is affected by deterioration processes and external loads. Both effects may change over time, posing a challenge for conducting reliability analysis. In such context, this contribution aims at assessing the reliability of structures where some of its parameters are modeled as random variables, possibly including deterioration processes, and which are subjected to stochastic load processes. The approach is developed within the framework of importance sampling and it is based on the concept of composite limit states, where the time-dependent reliability problem is transformed into a series system with multiple performance functions. Then, an efficient two-step importance sampling density function is proposed, which splits time-invariant parameters (random variables) from the time-variant ones (stochastic processes). This importance sampling scheme is geared towards a particular class of problems, where the performance of the structural system exhibits a linear dependency with respect to the stochastic load for fixed time. This allows calculating the reliability associated with the series system most efficiently. Practical examples illustrate the performance of the proposed approach.

AB - Structural performance is affected by deterioration processes and external loads. Both effects may change over time, posing a challenge for conducting reliability analysis. In such context, this contribution aims at assessing the reliability of structures where some of its parameters are modeled as random variables, possibly including deterioration processes, and which are subjected to stochastic load processes. The approach is developed within the framework of importance sampling and it is based on the concept of composite limit states, where the time-dependent reliability problem is transformed into a series system with multiple performance functions. Then, an efficient two-step importance sampling density function is proposed, which splits time-invariant parameters (random variables) from the time-variant ones (stochastic processes). This importance sampling scheme is geared towards a particular class of problems, where the performance of the structural system exhibits a linear dependency with respect to the stochastic load for fixed time. This allows calculating the reliability associated with the series system most efficiently. Practical examples illustrate the performance of the proposed approach.

KW - Composite limit state functions

KW - Cumulative failure probability

KW - Importance sampling

KW - Simulation-based method

KW - Stochastic load

KW - Time-variant structure

UR - http://www.scopus.com/inward/record.url?scp=85102972651&partnerID=8YFLogxK

U2 - 10.1016/j.ymssp.2021.107699

DO - 10.1016/j.ymssp.2021.107699

M3 - Article

AN - SCOPUS:85102972651

VL - 159

JO - Mechanical Systems and Signal Processing

JF - Mechanical Systems and Signal Processing

SN - 0888-3270

M1 - 107699

ER -