Abstract
Various definitions and methods have been used by researchers to predict the time-dependent reliability of structures. In the present study, these methods are first critically reviewed and examined. Among these methods, the stochastic-process-based method is theoretically the most rigorous but also computationally the most expensive. To facilitate the wide application of the stochastic-process-based method in complex problems, an efficient importance sampling method is then proposed in this paper. The proposed method includes a number of improvements formulated to enhance the efficiency and robustness of an existing method proposed by Kurtz and Song, leading to more efficient solutions of time-dependent reliability problems of structural systems with multiple important regions. The validity and efficiency of the new method is demonstrated through three numerical examples.
Original language | English |
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Pages (from-to) | 38-50 |
Number of pages | 13 |
Journal | Structural Safety |
Volume | 66 |
DOIs | |
Publication status | Published - 1 May 2017 |
Keywords
- Adaptive importance sampling
- Cross-entropy
- Gaussian mixture
- Monte Carlo simulation
- System reliability
- Time-dependent reliability
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Safety, Risk, Reliability and Quality