MICRO-CT IMAGE-BASED RECONSTRUCTION MODEL FOR FAILURE ANALYSIS OF SHEET MOLDING COMPOUND (SMC) COMPOSITES

Abstract

This research provides a multiscale framework of failure analysis for carbon-fiber sheet molding compound (CF-SMC) through a bundle packing reconstruction algorithm and material constitutive modeling, respectively. SMC composites have attracted the attention of many industries due to their high strength-to-weight ratio. However, depending on the speed and pressure in the manufacturing process, the spatially different flow patterns of fiber bundles lead to show inhomogeneous mechanical performance. This is because the location and orientation of fiber bundles in SMC composites have a significant role in mechanical behavior. Therefore, it is crucial to understand the effects of these parameters on mechanical behavior. Therefore, in this study, micro-CT imaging is performed to accurately determine SMC composites' internal geometry. The orientation and location of fiber bundles are statistically expressed as cumulative distribution function (CDF). Using these distributions as input, a mesoscale representative volume element (RVE) is constructed through a bundle packing reconstruction algorithm based on the random sequential adsorption (RSA) method. Furthermore, to demonstrate failure analysis of the SMC composites, constitutive modeling of each constituent is established. Consequently, the change of mechanical behavior is estimated under different manufacturing conditions.