Fretting fatigue crack propagation lifetime estimation using Long Short-Term Memory network
Authors:
- Can WangCan Wang
- Qiqi XiaoQXQiqi Xiao
- Yingjian GuoYGYingjian Guo
- Gang ChenGCGang Chen
- Lihua WangLihua Wang
- Magd Abdel WahabMWMagd Abdel Wahab
- 17 July 2025
- journal article
- Published by Elsevier in Engineering Fracture Mechanics
- Vol. 327
Abstract
No abstract availableFunding Information
- National Natural Science Foundation of China (12272270)
- Shanghai Key Basic Research Program
- China Scholarship Council (202008130124)
This publication has 30 references indexed in Scilit:
- Machine learning based framework for rapid forecasting of the crack propagationEngineering Fracture Mechanics, 2024
- Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learningFrontiers of Structural and Civil Engineering, 2024
- In-situ observation and finite element analysis of fretting fatigue crack propagation behavior in 1045 steelChinese Journal of Aeronautics, 2021
- An artificial neural network modeling approach for short and long fatigue crack propagationComputational Materials Science, 2020
- A data-driven approach based on long short-term memory and hidden Markov model for crack propagation predictionEngineering Fracture Mechanics, 2020
- Direction of crack propagation in a complete contact fretting-fatigue problemInternational Journal of Fatigue, 2014
- Experimental results in fretting fatigue with shot and laser peened Al 7075-T651 specimensInternational Journal of Fatigue, 2012
- A new fatigue frictional contact crack propagation model with the coupled X-FEM/LATIN methodComputer Methods in Applied Mechanics and Engineering, 2007
- Crack tip and associated domain integrals from momentum and energy balanceEngineering Fracture Mechanics, 1987
- A mixed-mode crack analysis of rectilinear anisotropic solids using conservation laws of elasticityInternational Journal of Fracture, 1980