Prediction of constant amplitude fatigue crack growth life of 2024 T3 Al alloy with R-ratio effect by GP
A genetic programming approach (GP) for predicting fatigue crack growth rate (da/dN) of Al-alloy has been described. The crack growth rate has been calculated by using an exponential model from experimental crack length (a) and number of cycles (N) data which has been subsequently used as training data base for GP model formulation along with load ratio (R), maximum stress intensity factor (Kmax) and stress intensity factor rage (?K). The validity of the proposed GP model has been confirmed by comparing the model prediction by experimental data and also with previously proposed ANN model.
fatigue crack growth life genetic programming fatigue crack growth rate load ratio artificial neural network