Details
| Original language | English |
|---|---|
| Article number | 107699 |
| Journal | Mechanical Systems and Signal Processing |
| Volume | 159 |
| Early online date | 24 Mar 2021 |
| Publication status | Published - Oct 2021 |
Abstract
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.
Keywords
- Composite limit state functions, Cumulative failure probability, Importance sampling, Simulation-based method, Stochastic load, Time-variant structure
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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In: Mechanical Systems and Signal Processing, Vol. 159, 107699, 10.2021.
Research output: Contribution to journal › Article › Research › peer review
}
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 -