Prediction on the ablative performance of carbon/carbon composites based on artificial neural network

The artificial neural network (ANN) method is applied to the prediction on the ablative performance of carbon/carbon composites. The key control factors for the ablative performance, namely, the density, degree of graphitization and the matrix kind, were selected. Further, a relation between those factors and ablative performance was determined. Through large numbers of experimental data, the structure and the performance of ANN had been evaluated with the variation of training parameters. It can be achieved from the results that there exists an optimal predicting ratio when the training set scale, the hidden unit, initial learning rate and momentum coefficient are 35, 7, 0.5 and 0.2, respectively. Based on the ratio, prediction and evaluation on the mass ablative rate have been made for the ablative performance of carbon/carbon composites. With the application of ANN, the prediction error is within 11%, which can satisfy the precision requirements for practical engineering purposes.