Colloquia

Samenvatting

Over the past century, advancements in material science and technology have led to the development of materials with improved performance and reduced costs. Composite materials have shown promising performance in the aerospace industry application due to their high strength-to-weight ratio and excellent fatigue resistance. Thermoplastic composites are gaining more interest over their thermoset counterparts due to their melt processability, which offers advantages in manufacturing and assembling large parts through cost-effective fusion bonding processes. Induction welding is an attractive assembly technology that uses the melt processability of the thermoplastic matrix to bond multiple parts. This technology uses an induction coil to generate heat in a workpiece by means of eddy currents, which rely on the conductive network of fibres within the composite material.

Simulating the heating mechanism during the induction welding would provide significant value in process window development and optimisation of the process. One of the input parameters in the simulation is the anisotropic conductivity of the composite material. While the conductivity in the fibre direction can be estimated using the rule of mixture, the in-plane transverse and through-thickness conductivity needs to be characterised experimentally. It has been observed that in these particular directions, the morphology of the material, which includes the fibre volume fraction and the quality of the fibre-to-fibre contact, plays an essential role in the low conductivity value obtained from the measurement.

This study focuses on the correlation between the fibre distribution in a 2D cross-sectional micrograph and the electrical conductivity of a unidirectional composite in the transverse direction. Several statistical descriptors were used to quantify the fibre distributions as obtained from microscopy. In addition, a quasi-3D resistor network was created based on the micrographs. The findings from this study suggest that 2D statistical spatial analysis is inadequate for assessing the correlation between the morphology and the measured electrical conductivity since it is limited to local fibre arrangements and short to medium-range distribution. Furthermore, the quasi-3D microstructure-based resistor network model seems to show a good preliminary approach to estimate the equivalent resistance value by considering threshold parameters based on inter-fibre distance and local fibre volume fraction within the microstructure. Further improvements to the model are necessary to build a more reliable model and ensure that the estimated resistance values are accurate.