Prediction of J-Integral dependence to residual stress and crack depth on NACA 0012-34 using FE and ANN

This paper presents an approach of linking finite element method with artificial neural network to predict J-Integral parameter in desirable airfoil condition. Finite Element (FE) and Artificial Neural Network (ANN) have been employed for the purpose. In other words, a prediction of finite element results has been done using ANN. Ultimately results of two methods have been compared for different cases. Wing fracture is a well-known problem of the planes which depends on various parameters. The J-integral is a vital parameter in evaluations of structure fracture phenomena. On the other hand residual stresses play an influential role in fracture formation. In the current work, effect of residual stresses and crack depth on J-Integral has been investigated in a standard NACA0012-34 airfoil. As will be seen, residual stresses and crack depth influence J-Integral values. It also will be shown that predictions of ANN method are in a good agreement with those obtained by finite element method.