Neuro-Fuzzy Modeling of Fatigue Life Prediction of Unidirectional Glass Fiber/Epoxy Composite Laminates

Abstract

Fatigue behavior of unidirectional glass fiber/epoxy composites under tension–tension and tension–compression loading is important in the design of composite structures. Adaptive neuro-fuzzy modeling was successfully used to model the relationship between the input/output variables of fatigue behavior of unidirectional glass fiber/epoxy composites. The experimental input variables were the maximum stress, fiber orientation, and stress ratio, while the output variable was the number of cycles to failure. In comparison with previous results obtained using neural networks only, the proposed hybrid neuro-fuzzy method gave more accurate fatigue life predictions.