Estimating the resistance of aging service-proven bridges with a Gamma process-based deterioration model

Cao Wang, Kairui Feng, Long Zhang, Aming Zou

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

The environmental or anthropogenic factors, to which the in-service bridges are subjected, are responsible for the reduction of bridge performance, and finally lead to great service risk for bridges and increase the probability of substantial economic losses. Probability-based estimate of bridge resistance is an essential indicator for the bridge condition evaluation and for optimization of bridge maintenance/repair decisions. It places an emphasis on the proper probabilistic models of structural properties and assessment methods. Making full use of historical service load information may improve the accuracy of bridge performance assessment with reduced epistemic uncertainty for existing aging bridges. In to-date analyses to update the bridge resistance with past service information, the models of resistance deterioration have been assumed as either deterministic or fully correlated, which may differ significantly from the realistic case. With this regard, this paper proposes a novel method for updating the resistance of service-proven bridges with a realistic deterioration model. The Gamma stochastic process has been suggested in the literature to describe the probabilistic behavior of structural time-dependent resistance and thus is adopted in this paper. An illustrative bridge is presented to demonstrate the applicability of the proposed method. Parametric examples are conducted to investigate the role of resistance deterioration model in the updated estimate of bridge resistance with historical service information.

Original languageEnglish
Pages (from-to)76-84
Number of pages9
JournalJournal of Traffic and Transportation Engineering
Volume6
Issue number1
DOIs
Publication statusPublished - Feb 2019
Externally publishedYes

Keywords

  • Bridge safety
  • Existing aging bridges
  • Gamma deterioration process
  • Historical load information
  • Resistance updating

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