Improving accuracy of mold filling simulation with experimental data

In this study, mold filling simulation was completed using two types of crystallization data inputs: typical crystallization data acquired using standard slow cooling techniques and experimental crystallization data generated across a range of cooling rates acquired by fast scanning chip calorimeter (FSC). The cooling rates achieved via FSC mimics those experienced by the polymer during the injection molding process. Results showed that experimental crystallization data successfully enhances simulation results to produce a gradient of crystallization from skin to core, which correlates well to the actual microstructure of physical molded samples.