Injection molding of polypropylene was conducted using a heating device to control mold surface temperature over time. By varying the temperature and heating times, a significant effect on cavity pressures, temperatures, and morphology distribution in the resulting samples was obtained. The University of Salerno's UNISA code, a simulation model for injection molding, was used to simulate the experimental conditions. This code incorporates a crystallization kinetics model that accounts for the competing formation of spherulites and fibrils from the same amorphous material, considering the effects of temperature, pressure, and flow evolution during different stages of the process. The simulation results showed good agreement with experimental data for temperature evolutions within the mold and pressure variations at critical points during the filling, packing, and cooling stages. Additionally, the simulation consistently predicted the formation of a fibrillar layer near the mold wall. Overall, a comprehensive framework for understanding and simulating the injection molding process is provided, with relevant implications for the optimization of manufacturing conditions and improving part quality.
Modeling spherulitic and fibrillar crystallization kinetics in injection molding: Analysis of process variables and morphological evolution
Speranza V.
;Liparoti S.;Titomanlio G.;Pantani R.
2024-01-01
Abstract
Injection molding of polypropylene was conducted using a heating device to control mold surface temperature over time. By varying the temperature and heating times, a significant effect on cavity pressures, temperatures, and morphology distribution in the resulting samples was obtained. The University of Salerno's UNISA code, a simulation model for injection molding, was used to simulate the experimental conditions. This code incorporates a crystallization kinetics model that accounts for the competing formation of spherulites and fibrils from the same amorphous material, considering the effects of temperature, pressure, and flow evolution during different stages of the process. The simulation results showed good agreement with experimental data for temperature evolutions within the mold and pressure variations at critical points during the filling, packing, and cooling stages. Additionally, the simulation consistently predicted the formation of a fibrillar layer near the mold wall. Overall, a comprehensive framework for understanding and simulating the injection molding process is provided, with relevant implications for the optimization of manufacturing conditions and improving part quality.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.