کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
495298 | 862822 | 2015 | 7 صفحه PDF | دانلود رایگان |

• 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 (ΔK).
• 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.
The objective of this study is to develop a genetic programming (GP) based model to predict constant amplitude fatigue crack propagation life of 2024 T3 aluminum alloys under load ratio effect based on experimental data and to compare the results with earlier proposed ANN model. It is proved that genetic programming can effectively interpret fatigue crack growth rate data and can efficiently model fatigue life of the material system under investigation in comparison to ANN model.
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Journal: Applied Soft Computing - Volume 26, January 2015, Pages 428–434