PREDICTION OF FATIGUE CRACK GROWTH BASED ON THE ANALYTICAL CRACK-CLOSURE MODEL AND NEURAL NETWORKS

Abstract

Abstract: The Newman analytical crack-closure model was used to compute the crack open stress and the crack growth rates. To reduce the computational time and increase the precision, a new method based on the neural networks is proposed to solve the compatible equations, the neural networks structure and parameters are given. It was used to predict crack growth under constant amplitude loading on 2219-T851 aluminum alloy plate material. The predicted crack growth lives agreed well with experimental data. The computational time is within an elapsed time of the circuit time-constant (ns).

Key words: Closure theory, Fatigue crack, Growth rates, Neural networks, Opening stress

CLC Number:

O346

Sun Daoheng;Hu Qiao;Xu Hao. PREDICTION OF FATIGUE CRACK GROWTH BASED ON THE ANALYTICAL CRACK-CLOSURE MODEL AND NEURAL NETWORKS[J]. , 1998, 34(5): 60-65.

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PREDICTION OF FATIGUE CRACK GROWTH BASED ON THE ANALYTICAL CRACK-CLOSURE MODEL AND NEURAL NETWORKS

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