Multi-scale digital image correlation for detection and quantification of matrix cracks in carbon fiber composite laminates in the absence and presence of voids controlled by the cure cycle

Abstract

Digital image correlation is applied to the images of a deforming composite to obtain strain maps at three length scales: micro-scale (ply level, hundreds of micrometers), meso-scale (laminate level, millimeters), and macro-scale (specimen level, tens of millimeters). The images are acquired in-situ with optical cameras and an electron microscope. The strain mapping at the macro- and meso-scales allows semi-automatic detection of matrix cracks and quantification of their density evolution in function of the applied strain. The micro-scale examination provides additional insights into the failure mechanisms. The technique is developed and then applied to characterize transverse cracking in cross-ply carbon fiber/epoxy composites in the absence and presence of manufacturing defects (including voids). Laminates with defects were produced by lowering the autoclave pressure and the cure temperature, intentionally. The strain for cracking onset and the saturation crack density are found to be different in the inner and outer transverse plies of both types of laminates. The change in processing conditions that led to the presence of voids and incomplete matrix cure resulted in a lower strain for cracking onset and up to 3.5 times increase of the crack density in comparison with the reference material without defects.