Fiber reinforced thermoplastic composites have shown to be attractive for industry as they can be reused, reshaped, welded and repaired, while keeping mechanical properties on par with thermoset composites. Since thermoplastics usually have high melt viscosities unsuitable for liquid composite molding processes, in-situ synthesis of PA6 from ε-caprolactam is considered. Its reactive mix has low viscosity which allows impregnation. However, the coupled crystallization and polymerization affects the resin viscosity and its flow is altered by the dual-scale permeability of the fiber preform. Thus, to predict the local differences in the thermoplastics properties, a coupled polymerization crystallization model needs to be integrated in the LCM processing simulation at representative scales. This study aims to propose a reliable simulation of the resin flow through a fibrous preform. Hence, viscosity measurements on the reactive mix are achieved using a rheometer with parallel-plate geometry, aiming to associate a viscosity model with the Hillier coupled polymerization-crystallization model previously determined by Vicard. The full chemorheological model will then be integrated into a simulation of LCM process in OpenFOAM®, an open source CFD software in order to follow the extent of the synthesis in the resin flow during the process. As a future work, simulations including microscale tow information extracted from a real textile specimen will permit to investigate the effect of permeability and double scale porosity in fibrous preforms on the final polymerization rate and crystallinity.

Variabilities in polyamide 6 (PA6) composite manufacturing by liquid processes can occur due to polymerization, crystallization, and flow through a fibrous preform. Numerical simulations of the process predicting the kinetics can facilitate manufacturing optimization. This study proposes an efficient modeling approach that can be integrated in current simulation discretization methods such as the finite volume method (FVM) while considering the interaction between PA6 polymerization and crystallization. Using polymerization and crystallization models issued from the literature, a previous study determined Hillier coupling method to be able to predict PA6 kinetics. A simpler and more efficient coupling will be introduced and adapted to account for process variability. It was integrated into an FVM framework for process simulation of injection showcasing the capabilities of the model to predict potential crystallization discrepancies.