2023
DOI: 10.1061/jmcee7.mteng-16335
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Fractographic Analysis and Particle Filter-Based Fatigue Crack Propagation Prediction of Q550E High-Strength Steel

Anyin Peng,
Yafei Ma,
Lei Wang
et al.
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Cited by 8 publications
(5 citation statements)
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“…Moreover, welding residual stress can be precisely forecasted by using the transverse and bending stress components derived from the transverse constraint, bending constraint, and welding residual stress as predictors for learning the DNN model. Also, results from a study showed that the FCG behavior of the butt-welded specimen is more sensitive to the stress ratio than that of the base metal specimen [131].…”
Section: Resultsmentioning
confidence: 99%
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“…Moreover, welding residual stress can be precisely forecasted by using the transverse and bending stress components derived from the transverse constraint, bending constraint, and welding residual stress as predictors for learning the DNN model. Also, results from a study showed that the FCG behavior of the butt-welded specimen is more sensitive to the stress ratio than that of the base metal specimen [131].…”
Section: Resultsmentioning
confidence: 99%
“…Subsequently, the reliability of the upgrade was upheld using Weibull models found in survival analysis. In research by Peng et al [131], they developed a particle-filter based Fatigue Crack Growth (FCG) prediction technique for a base metal and butt-welded specimen to deal with the uncertainty in the FCG process. Yu et al [132] developed a novel technique incorporating both ML and FEA to forecast F-N fatigue curves of high-strength steel RSW joints.…”
Section: Random/hybrid Based Methodsmentioning
confidence: 99%
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