Two Fatigue Life Prediction Models Based on the Critical Plane Theory and Artificial Neural Networks

Abstract

Since a multiaxial loading environment may lead to the fatigue failure of structures, establishing a reliable fatigue model to predict the multiaxial fatigue lives of structures has always been a concern of engineers. This study proposes a new multiaxial fatigue theoretical model (WYT model) based on the critical plane theory, which takes the plane of the maximum shear strain amplitude as the critical plane and considers the effects of shear stress and normal stress on fatigue damage. Moreover, a backpropagation neural network (BPNN) model for multiaxial fatigue life prediction with the shear strain amplitude, normal strain amplitude, mean shear stress, and mean normal stress on the same critical plane as input parameters and fatigue life as the output variable is established. Finally, the WYT model and the BPNN model are compared with two existing multiaxial fatigue models to evaluate the life prediction effects of different models for S45C and 7075-T651 under constant-amplitude and variable-amplitude multiaxial loadings. The calculation results show that the WYT model is feasible, and the BPNN model is more accurate in predicting the fatigue lives of specimens than other multiaxial fatigue theoretical models.

Keywords

• multiaxial fatigue
• critical plane theory
• fatigue life prediction
• neural network
• fatigue damage