Infusion Simulation of Graphene-Enhanced Resin in LCM for Thermal and Chemo-Rheological Analysis.

The present numerical study proposes a framework to determine the heat flow parameters-specific heat and thermal conductivity-of resin-graphene nanoplatelets (GNPs) (modified) as well as non-modified resin (with no GNPs). This is performed by evaluating the exothermic reaction which occurs during both the filling and post-filling stages of Liquid Composite Moulding (LCM). The proposed model uses ANSYS Fluent to solve the Stokes-Brinkman (momentum and mass), energy, and chemical species conservation equations to a describe nano-filled resin infusion, chemo-rheological changes, and heat release/transfer simultaneously on a Representative Volume Element (RVE). The transient Volume-of-Fluid (VOF) method is employed to track free-surface propagation (resin-air interface) throughout the computational domain. A User-Defined Function (UDF) is developed together with a User-Defined Scaler (UDS) to incorporate the heat generation (polymerisation), which is added as an extra source term into the energy equation. A separate UDF is used to capture intra-tow (microscopic) flow by adding a source term into the momentum equation. The numerical findings indicate that the incorporation of GNPs can accelerate the curing of the resin system due to the high thermal conductivity of the nanofiller. Furthermore, the model proves its capability in predicting the specific heat and thermal conductivity of the modified and non-modified resin systems utilising the computed heat of reaction data. The analysis shows an increase of ∼15% in the specific heat and thermal conductivity due to different mould temperatures applied (110-170 °C). This, furthermore, stresses the fact that the addition of GNPs (0.2 wt.%) improves the resin-specific heat by 3.68% and thermal conductivity by 58% in comparison to the non-modified thermoset resin. The numerical findings show a satisfactory agreement with and in the range of experimental data available in the literature.