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Author:

Wu, Jieqiong (Wu, Jieqiong.) | Zhang, Bochao (Zhang, Bochao.) | Xu, Jianchao (Xu, Jianchao.) | Jin, Liu (Jin, Liu.) | Diao, Bo (Diao, Bo.)

Indexed by:

EI Scopus SCIE

Abstract:

A probabilistic fatigue life prediction model for RC beams under chloride environment is proposed, and the statistical uncertainty is considered by Bayesian inference to determine and update model parameters. In terms of the sparse fatigue data, the Markov-chain Monte-Carlo (MCMC) method is utilized to conduct the Bayesian updating. The prior distribution and posterior distributions are respectively determined by the data in this study and open references. Results show that the fatigue life under chloride environment is accurately predicted by a probabilistic S-N curve, in which as update points increase, predictions get close to tests and the statistical uncertainty is reduced.

Keyword:

Bayesian updating Chloride environment Fatigue life prediction MCMC method RC beams

Author Community:

  • [ 1 ] [Wu, Jieqiong]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 2 ] [Jin, Liu]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 3 ] [Zhang, Bochao]Univ Calgary, Data Sci & Analyt, Calgary, AB T2N 1N4, Canada
  • [ 4 ] [Xu, Jianchao]China Acad Railway Sci Co Ltd, Railway Engn Res Inst, Beijing 100081, Peoples R China
  • [ 5 ] [Diao, Bo]Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China

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Source :

INTERNATIONAL JOURNAL OF FATIGUE

ISSN: 0142-1123

Year: 2023

Volume: 173

6 . 0 0 0

JCR@2022

ESI Discipline: MATERIALS SCIENCE;

ESI HC Threshold:26

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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