Probabilistic demand models and fragility estimates for bridges elevated with steel pedestals

Vahid Bisadi, Paolo Gardoni, Monique Head

Research output: Contribution to journalArticlepeer-review

Abstract

Probabilistic seismic demand models are developed for bridges elevated with steel pedestals by adding correction and error terms to commonly used models. Separate probabilistic demand models are developed for the force demand on steel pedestals and the shear and deformation demands on concrete columns. Nonlinear time history analyses on detailed, three-dimensional finite-element models are used to generate virtual experimental data. By applying a Bayesian updating method to the generated data, parameters of the probabilistic models and their correlations are estimated. Comparisons between the demands from the developed probabilistic demand models and the demands from their corresponding demand models without correction and error terms reveal that the developed probabilistic models provide more accurate and unbiased predictions of the demands of interest. As an illustration of the developed framework, fragilities are estimated for a two-span bridge. The results show that pedestals are more vulnerable in the longitudinal direction, and columns are more vulnerable in the transverse direction. A sensitivity analysis on the studied bridges shows that decreasing the pedestal height, increasing the length of the pedestal anchor bolts within the concrete bent, and increasing the concrete cover on the anchor bolts are the most effective ways to decrease the probability of failure.

Original languageEnglish (US)
Pages (from-to)1515-1528
Number of pages14
JournalJournal of Structural Engineering (United States)
Volume139
Issue number9
DOIs
StatePublished - Sep 1 2013

Keywords

  • Bridges
  • Demand
  • Estimation
  • Probability
  • Steel pedestals

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering

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