Although gas-assisted injection molding (GAIM) has been practiced in industry for more than a decade, the process is not completely understood, particularly with respect to the gas penetration mechanism. Consequently, mold design and process control are often governed by trial-and-error, and reliable information on the gas distribution and the final product properties can often only be obtained from experiments. To gain a better understanding of the gas-assisted injection molding process, we have developed a computational model for the GAIM process. This model has been set up to deal with (non-isothermal) three-dimensional flow, in order to correctly predict the gas distribution in GAIM products. It employs a pseudo-concentration method, in which the governing equations are solved on a fixed grid that covers the entire mold. Both the air downstream of the polymer front and the gas are represented by a fictitious fluid that does not contribute to the pressure drop in the mold. The model has been validated against both isothermal and non-isothermal gas injection experiments. In contrast to other models that have been reported in the literature, our model yields the gas penetration from the actual process physics (not from a presupposed gas distribution). Consequently, it is able to deal with the 3-D character of the process, as well as with primary (end of gas filling) and secondary (end of packing) gas penetration, including temperature effects and generalized Newtonian viscosity behavior.
¡ Present affiliation: Unilever Research