Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …

Neural network (NN) models have significantly impacted fatigue‐related engineering
communities and are expected to increase rapidly due to the recent advancements in …

Fibre composite materials (FCMs) are widely used in the aerospace, military defence, and
engineering manufacturing industries due to their high strength and high modulus …

The influence of the constant life diagram (CLD) formulation on the fatigue life prediction of
composite materials was examined. Most commonly used and recently proposed CLDs …

The present study introduces an artificial neural network (ANN) model coupled with the non-
dominated sorting genetic algorithm (NSGA-II) to establish an advanced model for fatigue …

Ceramic matrix composites have been widely applied in the aerospace field due to the
excellent mechanical properties. However, the complex microstructure and failure …

A new formulation for predicting an asymmetric, piecewise non-linear constant life diagram
(CLD) is introduced in this paper. The development of the new model is based on the …

The effect of mean load on the fatigue behavior of adhesively-bonded pultruded GFRP
double-lap joints under constant amplitude loading was experimentally investigated. The …

To study the fatigue behavior of composites, a large number of experimental assays for both
deterministic and probabilistic analysis are needed. Recent studies have demonstrated …

Abstract Artificial Neural Networks (ANN) have been successfully used in predicting the
fatigue behavior of fiber-reinforced composite materials. In most cases, the predictions were …