The Impact of Pressure-Dependent Viscosity Data on Injection Molding Simulations of Highly Filled Thermoplastics

The injection compression molding using dynamic mold control (ICM-DT) represents a promising technological approach to the manufacturing of highly filled, modified thermoplastic components with tight geometric tolerances. While the numerical prediction of flow states is, to date, predominantly based on the Cross-WLF modeling of viscoelastic characteristics of the melt, new material-related developments necessitate the assessment of process- and material-related boundaries. The present paper employs a highly filled graphite-polypropylene system, exhibiting a graphite mass fraction of 80%, for the quantitative comparison of Cross-WLF predictions and experimentally derived flow states. Based on coupled counter pressure-chamber high-pressure capillary rheometry (CPC-HCR) and counterpressurized viscometry (CPV) alongside the ICM-DT of thin-walled specimens, pressure-induced crystallization was identified to induce significant deviations from Cross-WLF predictions. Cross-WLF modeling strongly overestimates the processability of the applied graphite-polypropylene system under both injection molding (IM) and ICM regimes. We therefore observe a predominant influence of pressure-induced crystallization mechanisms in dynamic mold temperature process domains, in which the pressure-induced, crystallization-related exponential viscosity increase cannot be adequately modeled through both pressure-dependent and pressure-agnostic Cross-WLF models. The numerical approximation of flow states under dynamic mold temperature regimes hence necessitates the consideration of solidification-induced, self-intensifying pressure excursions.