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摘要:
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.
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来源 :
INTERNATIONAL JOURNAL OF FATIGUE
ISSN: 0142-1123
年份: 2023
卷: 173
6 . 0 0 0
JCR@2022
ESI学科: MATERIALS SCIENCE;
ESI高被引阀值:26
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