Data-driven approach to very high cycle fatigue life prediction

Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next

Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo et al. · Journal of Scientific Computing · 2022 · 2.3K citations · Full text

Computing, Computer Science, Physics +16

Characteristic S–N properties of high‐carbon–chromium‐bearing steel under axial loading in long‐life fatigue

Tatsuo Sakai, Yosuke Sato, Noriyasu OGUMA · Fatigue & Fracture of Engineering Materials & Structures · 2002 · 347 citations

Engineering, Materials Engineering, Materials Science +17

Machine learning based fatigue life prediction with effects of additive manufacturing process parameters for printed SS 316L

Zhixin Zhan, Hua Li · International Journal of Fatigue · 2020 · 297 citations

Engineering, Materials Engineering, Materials Science +15

Fatigue life and mechanistic modeling of interior micro-defect induced cracking in high cycle and very high cycle regimes

Ming‐Liang Zhu, Fu‐Zhen Xuan · Acta Materialia · 2018 · 261 citations

Natural Sciences, Materials Engineering, Materials Science +17

Machine learning-based fatigue life prediction of metal materials: Perspectives of physics-informed and data-driven hybrid methods

Haijie Wang, Bo Li, Jian‐Guo Gong et al. · Engineering Fracture Mechanics · 2023 · 249 citations

Natural Sciences, Materials Engineering, Materials Science +14