A Study on the Prediction of Fatigue Damage in 2024-T3 Aluminium Alloy Using Neural Networks

신경회로망을 이용한 AI 2024-T3합금의 피로손상예측에 관한 연구

Fatigue damage is the phenomena which is accumulated gradually with loading cycle in material. It is represented by fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$. Fracture mechanical parameters estimating large crack growth behavior can calculate quantitative amount of fatigue crack growth resistance in engineering material. But fatigue damage has influence on various load, material and environment. Therefore, In this study, we propose that artificial intelligent fatigue damage model can predicts fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$ simultaneously using fracture mechanical and nondestructive parameters.