Mechanical Engineering Commons^™

Identifying Fibre Orientations For Fracture Process Zone Characterization In Scaled Centre-Notched Quasi-Isotropic Carbon/Epoxy Laminates With A Convolutional Neural Network, Xiaodong Xu, Aser Abbas, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

This paper presents a novel X-ray Computed Tomography (CT) image analysis method to characterize the Fracture Process Zone (FPZ) in scaled centre-notched quasi-isotropic carbon/epoxy laminates. A total of 61 CT images of a small specimen were used to fine-tune a pre-trained Convolutional Neural Network (CNN) (i.e., VGG16) to classify fibre orientations. The proposed CNN model achieves a 100% accuracy when tested on the CT images of the same scale as the training set. However, the accuracy drops to a maximum of 84% when tested on unlabelled images of the specimens having larger scales potentially due to their lower resolutions. Another …