In injection molding, the pressure in the cavity usually reaches the atmospheric pressure before the ejection, therefore the thermal contact between polymer and mold is modified. This paper aims to evaluate the nature of the thermal contact between the polymer and the mold during the holding and cooling phase. An experimental plate mold has been designed to study this phenomenon. Thermal sensors facing each other and pressure sensors have been set in the mold. An inverse method is used to determine the heat flux density crossing the polymer mold interface, and the mold surface temperature. Then, a second inverse algorithm allows to determine the temperature profile at the end of the filling and the time evolution of the thermal contact resistance (TCR). Finally, the polymer temperature distribution in the thickness is determined between the thermal sensors. The results of this study show that the TCR between the polymer and the mold is not negligible and not constant with time. The polymer temperature at the surface can be 20°C higher than the mold surface temperature. Moreover, asymmetric air gaps have been observed when cavity pressure becomes equal to atmospheric pressure, therefore asymmetric temperature profile in the thickness are generated.
In this study, the effective thermal conductivity tensor of carbon/epoxy laminates was investigated experimentally in the three states of a typical LCM-process: dry-reinforcement, raw and cured composite. Samples were made of twill-weave carbon fabric impregnated with epoxy resin. The transverse thermal conductivity was determined using a classical estimation algorithm, whereas a special testing apparatus was designed to estimate in-plane conductivity for different temperatures and different states of the composite. Experimental results were then compared to modified Charles & Wilson and Maxwell models. The comparison showed clearly that these models can be used to accurately and efficiently predict the effective thermal conductivities of wovenreinforced composites.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.