Fatigue Crack Growth Predictions in Aging Aircraft Panels Using Optimization Neural Network

An optimization-based neural network method is developed to predict fatigue crack growth and fatigue life of multiple site damage panels found in aging aircraft. The method utilizes an optimization solution to predict the probable crack path based upon the initial panel configuration and accounts for lead crack spanning, small multiple site damage, and plasticity zones. The approach of the neural network was motivated by the optimization analysis and the time-consuming computational analyses for multiple site damage problems.