Probabilistic capacity models and fragility estimates for reinforced concrete columns based on experimental observations

Paolo Gardoni, Armen Der Kiureghian, Khalid M. Mosalam

Research output: Contribution to journalArticle

Abstract

A methodology to construct probabilistic capacity models of structural components is developed. Bayesian updating is used to assess the unknown model parameters based on observational data. The approach properly accounts for both aleatory and epistemic uncertainties. The methodology is used to construct univariate and bivariate probabilistic models for deformation and shear capacities of circular reinforced concrete columns subjected to cyclic loads based on a large body of existing experimental observations. The probabilistic capacity models are used to estimate the fragility of structural components. Point and interval estimates of the fragility are formulated that implicity or explicity reflect the influence of epistemic uncertainties. As an example, the fragilities of a typical bridge column in terms of maximum deformation and shear demands are estimated.

Original languageEnglish (US)
Pages (from-to)1024-1038
Number of pages15
JournalJournal of Engineering Mechanics
Volume128
Issue number10
DOIs
StatePublished - Oct 1 2002
Externally publishedYes

Keywords

  • Capacity
  • Concrete
  • Concrete columns
  • Cyclic loads
  • Deformation
  • Models
  • Probability
  • Reinforced

ASJC Scopus subject areas

  • Mechanical Engineering

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