Fatigue Life Assessment of Polymer-Matrix Composites Under Variable Amplitude Loading Using Neural Networks - Hidayat, Mas Irfan Purbawanto Hidayat (2009)
In the current study, Multi Layer Perceptron (MLP) based neural networks (NN) model with one hidden layer was utilized to predict fatigue lives of polymer-matrix composites under wide spectrum of fatigue stress ratios. E-glass/epoxy (Material I), E-glass/polyester (Material II) and AS4/PEEK (Material III) composites with, respectively, six, nine and six stress ratio values from the corresponding fatigue database were employed. Two stress ratios of each material were selected as the training set which represented a limited set of stress ratios. The Levenberg-Marquardt training algorithm which implemented Bayesian regularization was utilized to deal with the limited training set. In addition, the quality of the fatigue lives predicted by the NN model compared to those obtained by the experiments or other method was measured using mean square error (MSE) value.