A phase field and deep-learning based approach for accurate prediction of structural residual useful life

In this work, we proposed a novel approach for the prediction of residual useful life (RUL) of structures through appropriately combining the phase field method and deep-learning. In this new approach, the phase field method is firstly utilized to obtain the structural responses of crack growth, which are further preserved as images. Then, the convolutional neural network (CNN) is constructed to establish a predictive model. The proposed...