Email this article and Applied Mechanics
56, 4, pp. 1109-1122, Warsaw 2018
DOI: 10.15632/jtam-pl.56.4.1109
Life prediction for LY12CZ notched plate based on the continuum damage mechanics and the genetic algorithm and radial basis function method
Genetic Algorithm and Radial Basis Function neural network method (GARBF) is propo-
sed to predict fatigue life of LY12CZ notched plate. Firstly, the multiaxial fatigue damage
evolution equation is derived, and the fatigue life of the notched specimen is predicted based
on the CDM method. Secondly, the RBF method is introduced to modify the relative devia-
tion between the theoretical result and actual life. According to the drawbacks of the RBF
method, the GA is adopted to optimize network parameters to effectively improve the model
quality and reduce the training error. Then, the verification test indicates that the combined
method of CDM and GARBF is able to reduce the average relative error of the results of
fatigue life prediction to about 7%, which shows that the new method to predict the fatigue
life is more reliable. At last, compared with the predicted results of the traditional Back
Propagation (BP) neural network, the GARBF model proposed in this paper has a better
optimization effect and the result is more stable. This research provides a feasible way to
predict the fatigue lives of the notched plate based on the CDM and GARBF method.
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