Fatigue behavior analysis and life evaluation method of building steel under the influence of multiple factors

Pan, Xuemei; Liu, Jianhui; Li, Youtang; Ren, Junqiang; Wang, Qi; Chen, Xiaochuang

doi:10.1016/j.engfracmech.2024.110116

Engineering Fracture Mechanics

2024

DOI: 10.1016/j.engfracmech.2024.110116

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Fatigue behavior analysis and life evaluation method of building steel under the influence of multiple factors

Xuemei Pan,

Jianhui Liu,

Youtang Li

et al.

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2024

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Cited by 2 publications

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Corrosion fatigue life prediction method of aluminum alloys based on back-propagation neural network optimized by Improved Grey Wolf optimization algorithm

Ji,

Li,

et al. 2024

J Mater Sci

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Corrosion fatigue life prediction method of aluminum alloys based on back-propagation neural network optimized by Improved Grey Wolf optimization algorithm

Ji,

Li,

et al. 2024

J Mater Sci

View full text Add to dashboard Cite

Multiaxial low-cycle fatigue life model for notched specimens considering small sample characteristics

Wu,

Liu,

Wang

et al. 2024

IJSI

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PurposeSufficient sample data are the necessary condition to ensure high reliability; however, there are relatively poor fatigue test data in the engineering, which affects fatigue life's prediction accuracy. Based on this, this research intends to analyze the fatigue data with small sample characteristics, and then realize the life assessment under different stress levels.Design/methodology/approachFirstly, the Bootstrap method and the principle of fatigue life percentile consistency are used to realize sample aggregation and information fusion. Secondly, the classical outlier detection algorithm (DBSCAN) is used to check the sample data. Then, based on the stress field intensity method, the influence of the non-uniform stress field near the notch root on the fatigue life is analyzed, and the calculation methods of the fatigue damage zone radius and the weighting function are revised. Finally, combined with Weibull distribution, a framework for assessing multiaxial low-cycle fatigue life has been developed.FindingsThe experimental data of Q355(D) material verified the model and compared it with the Yao’s stress field intensity method. The results show that the predictions of the model put forward in this research are all located within the double dispersion zone, with better prediction accuracies than the Yao’s stress field intensity method.Originality/valueAiming at the fatigue test data with small sample characteristics, this research has presented a new method of notch fatigue analysis based on the stress field intensity method, which is combined with the Weibull distribution to construct a low-cycle fatigue life analysis framework, to promote the development of multiaxial fatigue from experimental studies to practical engineering applications.

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Fatigue behavior analysis and life evaluation method of building steel under the influence of multiple factors

Cited by 2 publications

References 21 publications

Corrosion fatigue life prediction method of aluminum alloys based on back-propagation neural network optimized by Improved Grey Wolf optimization algorithm

Corrosion fatigue life prediction method of aluminum alloys based on back-propagation neural network optimized by Improved Grey Wolf optimization algorithm

Multiaxial low-cycle fatigue life model for notched specimens considering small sample characteristics

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