研究论文
A Bayesian physics-informed neural network model for probabilistic fatigue life assessment considering the size effect in additively manufactured materials
Qia Zhao, Jing Cao, Boda Wang, Yuan Tao, Xiang Xie, Weixing Yao
State Key Laboratory of Mechanical Structure Mechanics and Control Nanjing University of Aeronautics and Astronautics
来源International Journal of Fatigue
年份2026
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学术脉络
学科主题
工程Additive Manufacturing Materials and Processes
Fatigue and fracture mechanics · High Temperature Alloys and Creep
参考文献 38
Bayesian neural network approach to short time load forecasting
被引 189Philippe Lauret, Éric Fock, Rija N. Randrianarivony · Energy Conversion and Management · 2007
Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens
被引 80H.Y. Wan, G.F. Chen, C.P. Li · Journal of Material Science and Technology · 2018
Experimental investigation of the size effect in high cycle fatigue: Role of the defect population in cast aluminium alloys
被引 80Driss El Khoukhi, Franck Morel, Nicolas Saintier · International Journal of Fatigue · 2019
此处列出前 3 条
引用本文 6
A self-heating-based physics-guided neural network for fatigue life prediction of polymer matrix composites
被引 1Aravind Premanand, Gaurav Sharma, Frank Balle · Materials & Design · 2026
Key factors governing bending fatigue behavior and its evaluation methods in metal additive manufacturing: a review
被引 1Rongji Tang, Zainuddin Bin SAJURI, Peikai Zhang · Frontiers in Mechanical Engineering · 2026
An adaptive Bayesian Physics-Informed neural network model for predicting the fatigue life of high-strength steel under non-uniform corrosion
被引 1Xuanrui Yu, Qianling Wang, Nima Khodadadi · Computer-Aided Civil and Infrastructure Engineering · 2026
按被引量排序,此处列出前 3 条