Towards reliability evaluation involving correlated multivariates under incomplete probability information: A reconstructed joint probability distribution for isoprobabilistic transformation

Fan Wang, Heng Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)


The widely used Nataf transformation inherently assumes a normal copula for dependence modeling, which can be inappropriate in some cases. This paper aims to provide a more general isoprobabilistic transformation method for reliability evaluations under incomplete probability information. To this end, the joint probability distribution is represented using the pair-copula decomposition approach, which is highly flexible in dependence modeling. The desired pair-copula parameters are retrieved from the incomplete probability information by a simulation-based method. Finally, based on the reconstructed joint probability distribution, the Rosenblatt's transformation is adopted for the subsequent reliability evaluation. The proposed method is illustrated in a tunnel excavation reliability problem. Several dependence structures characterized by different pair-copulas are investigated to provide insights into the effect of copula selection on reliability results.
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalStructural Safety
Publication statusPublished - 1 Nov 2017


  • Correlated multivariates
  • Incomplete probability information
  • Pair-copulas
  • Reliability
  • Rosenblatt's transformation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Safety, Risk, Reliability and Quality

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