Physics-Informed Transfer Learning Model for Fatigue Life Prediction of In718 Alloy

Author:

Zhang Jianfeng,Chen Baihan,Zhang Guangping,Zhou Shangcheng,Xu Fang

Publisher

Elsevier BV

Reference39 articles.

1. Fatigue damage detection and risk assessment via neural network modeling of ultrasonic signals[J];H Alqahtani;Fatigue & Fracture of Engineering Materials & Structures,2022

2. Small data machine learning in materials science;Ji X B Xu P C;Npj Computational Materials

3. Data-driven machine learning for alloy research: Recent applications and prospects;Gao X Y;Materials Today Communications,2023

4. A neural network approach to fatigue life prediction[J];Pujol J C F;International Journal of Fatigue,2011

5. Polymer gear contact fatigue reliability evaluation with small data set based on machine learning[J];Liu G S;Journal of Computational Design and Engineering

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