Sheet Moulding Compound (SMC) based composites have a large potential in industrial contexts due to the possibility of achieving comparatively short manufacturing times. It is however necessary to be able to numerically predict both mechanical properties as well as manufacturability of parts.

In this paper a fully 3D, semi-empirical model based on fluid mechanics for the compression moulding of SMC is described and discussed, in which the fibres and the resin are modelled as a single, inseparable fluid with a viscosity that depends on volume fraction of fibres, shear strain rate and temperature. This model is applied to an advanced carbon-fibre SMC with a high fibre volume fraction (35%). Simulations are run on a model of a squeeze test rig, allowing comparison to experimental results from such a rig. The flow data generated by this model is then used as input for an Advani-Tucker type of model for the evolution of the fibre orientation during the pressing process. Numerical results are also obtained from the software 3DTimon. The resulting fibre orientation distributions are then compared to experimental results that are obtained from microscopy. The experimental measurement of the orientation tensors is performed using the Method of Ellipses. A new, automated, accurate and fast method for the ellipse fitting is developed using machine learning. For the studied case, comparison between the experimental results and numerical methods indicate that 3D Timon better captures the random orientation at the outer edges of the circular disc, while 3D CFD show larger agreement in terms of the out-of-plane component. One of the advantages of the new image technique is that less work is required to obtain microscope images with a quality good enough for the analysis.