Probabilistic fatigue life prediction for concrete bridges using Bayesian inference

Ming Yuan, Yun Liu, Donghuang Yan, Yongming Liu

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

A probabilistic fatigue life prediction framework for concrete bridges is proposed in this study that considers the stress history from the construction stage to the operation stage. The proposed fatigue analysis framework combines the fatigue crack growth-based material life prediction model and a nonlinear structural analysis method. A reliability analysis is proposed using the developed probabilistic model to consider various uncertainties associated with the fatigue damage. A Bayesian network is established to predict the fatigue life of a concrete bridge according to the proposed framework. The proposed methodology is demonstrated using an experimental example for fatigue life prediction of a concrete box-girder. Comparison with experimental data of fatigue life shows a satisfactory accuracy using the proposed methodology, and the ratio of the posterior predicted mean (updating time n = 8) to the test value decreases to 33%–1% in the current investigation.

Original languageEnglish (US)
Pages (from-to)765-778
Number of pages14
JournalAdvances in Structural Engineering
Volume22
Issue number3
DOIs
StatePublished - Feb 1 2019

Keywords

  • Bayesian network
  • bridge
  • concrete
  • fatigue life prediction
  • nonlinear

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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