Consideration of modeled pressure dependent viscosity data in injection molding simulation

Abstract The accuracy of injection molding simulations is largely dependent on the quality of the material data on which the flow calculations are based. Viscosity, as a measure of flow resistance in a plastic melt, is a key material property that significantly affects simulation results, especially the simulated injection pressure. The melt viscosity of a polymer is largely dependent on three factors: temperature, shear rate and pressure. A conventional high-pressure capillary rheometer (HPCR) can be used to measure viscosity in a shear rate range relevant for injection molding as a function of temperature and shear rate. However, conventional HPCR cannot determine the pressure dependence. Special devices, such as back pressure viscometers or back pressure chamber extensions, are required for this, but they are rarely available. Additionally, these measurements are time-consuming and expensive, which is why pressure-dependent viscosity data are rarely available. In this study, pressure-dependent viscosity data are calculated via a correlation between conventional viscosity data and pressure dependent melt density, utilizing the free volume approach based on the Simha & Somcynski equations of state (Simha, R. and Somcynsky, T. (1969). On the statistical thermodynamics of spherical and chain molecule fluids.Macromolecules 2: 342–350, doi: 10.1021/ma60010a005.). The advantage of this model calculation is that it is based on existing material data and is therefore particularly cost-effective. Subsequently, injection molding simulations of a mold with a hot runner manifold were carried out for both amorphous and semi-crystalline thermoplastics, using two different widely used commercial software solutions. The simulations were carried out using conventional pressure independent viscosity data and model-calculated pressure dependent viscosity data. Injection pressures were compared, revealing significantly higher injection pressures for amorphous polymers based on pressure-dependent data. Additionally, experimental injection molding tests were performed at simulated operating points to evaluate improvements in simulation accuracy.