Cross-entropy-based adaptive importance sampling for time-dependent reliability analysis of deteriorating structures

David Y. Yang, Jinguang Teng, Dan M. Frangopol

Research output: Journal article publicationJournal articleAcademic researchpeer-review

38 Citations (Scopus)


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 languageEnglish
Pages (from-to)38-50
Number of pages13
JournalStructural Safety
Publication statusPublished - 1 May 2017


  • 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


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