Prediction of contact lengths between an elastic layer and two elastic circular punches with neural networks

This paper explores the potential use of neural networks (NNs) in the field of contact mechanics. A neural network model is developed for predicting, with sufficient approximation, the contact lengths between the elastic layer and two elastic circular punches. A backpropagation neural network of three layers is employed. First contact problem is solved according to the theory of elasticity with integral transformation technique, and then the results are used to train the neural network. The effectiveness of different neural network configurations is investigated. Effect of parameters such as load factor, elastic punch radii and flexibilities that influence the contact lengths is also explored. The results of the theoretical solution and the outputs generated from the neural network are compared. Results indicate that NN predicted the contact length with high accuracy. It is also demonstrated that NN is an excellent method that can reduce time consumed.