Neural-Network Prediction of the Low-Temperature Fatigue Strength of Metals

A smart system for predicting the fatigue strength of metals over a broad temperature range is developed on the basis of a specially trained neural network. The system can predict the number of loading cycles to failure and also the onset of fatigue-crack formation and the rate of crack growth in different test conditions, including low temperatures.