Bulletin of Earthquake Engineering

, Volume 17, Issue 2, pp 927–955 | Cite as

Seismic fragility assessment of highway bridges using D-vine copulas

  • Tong ZhouEmail author
  • Ai-Qun Li
Original Research


Seismic vulnerability of highway bridges is crucial to the seismic risk assessment of highway transportation networks. A new framework for developing the fragility function at the system level utilizing the D-vine copula theory is proposed. In this methodology, first, the joint probabilistic seismic demand model (JPSDM), which represents the conditional joint distribution of various engineering demand parameters (EDPs) under each intensity measure (IM) level, is constructed using the D-vine approach; then, sample realizations of both the established JPSDM and capacity models of these considered components are compared to derive the system-level fragility curves. This methodology is illustrated in a typical two-span RC continuous girder-box bridge case, where pier columns, elastomeric pad bearings, the sliding bearings, and the abutments in both passive and active directions are considered as the major components. The results demonstrate that the performance of the optimal D-vine for characterizing the dependence structure among various EDPs is relatively superior in comparison with commonly-utilized multivariate standard copulas. The combination of the quantitatively-identified optimal D-vine copula and their conditional lognormal marginal distributions is adequate to construct the JPSDM of these five EDPs. Furthermore, the effects of different copula selections on the overall system vulnerability are well captured, which highlight the necessity for quantitative identification of the optimal D-vine copula for modeling the correlations among various EDPs.


Seismic vulnerability Highway bridges D-vine copulas System-level 



This investigation was supported by the National Natural Science Foundation of China (Grant No. 51438002).


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.College of Civil EngineeringTongji UniversityShanghaiChina
  2. 2.School of Civil EngineeringSoutheast UniversityNanjingChina
  3. 3.Beijing Advanced Innovation Center for Future Urban DesignBeijing University of Civil Engineering and ArchitectureBeijingChina

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