On the influence of rectangular Z-pins parameters on mode II delamination resistance of through the thickness reinforced composites

Z-pinned composites are an important class of materials increasingly used in the aerospace applications, civil construction, and automotive industry. Although many numerical and experimental studies exist on this topic, few of these employ modern and efficient computational techniques. This study presents, for the first time in the literature a study using Artificial Neural Networks (ANN) to predict mode II interlaminar fracture toughness in composite materials using z-pinned composites. Z-pins with different rectangular shapes and pin area densities are manufactured with design variables generated from Design of Experiments (DOE). The experimental results presented an improvement in the z-pinned mode II delamination resistance specimens in comparison to the unpinned. Thus, the Response Surface Model (RSM) and Analysis of Variance (ANOVA) are used to support a detailed statistical discussion of the experimental results. Also, the generated data are used to training an Artificial Neural Network, which is applied to predict and assess the influence of the pin size and density configuration on the interlaminar fracture properties of z-pinned composite structures.