Probabilistic seismic demand models and fragility estimates for RC bridges

Paolo Gardoni, Khalid M. Mosalam, Armen Der Kiureghian

Research output: Contribution to journalArticlepeer-review


A Bayesian methodology to construct probabilistic seismic demand models for the components of a structural system is developed. Existing deterministic models and observational data are used. The demand models are combined with previously developed capacity models for reinforced concrete (RC) bridge columns to estimate the seismic fragilities of bridge components and systems. The approach properly accounts for all relevant uncertainties, including model error. Application to two bridge examples typical of modern California practice is presented.

Original languageEnglish (US)
Pages (from-to)79-106
Number of pages28
JournalJournal of Earthquake Engineering
Issue numberSPEC. 1
StatePublished - 2003
Externally publishedYes


  • Bayesian inference
  • Bridges
  • Deformation demand
  • Demand models
  • Experimental data
  • Fragility
  • Model error
  • Model updating
  • Parameter estimation
  • Probabilistic models
  • Reinforced concrete
  • Shear demand
  • Uncertainty analysis

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Geotechnical Engineering and Engineering Geology


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