Determination of the pressure dependence of polymer melt viscosity using a combination of oscillatory and capillary rheometer

Abstract

For an accurate simulation of a high‐pressure injection molding process by using the CAE software, it is important to understand the pressure sensitivity of a polymer's melt viscosity. The current work describes a method for the determination of the pressure dependence parameter D3 of the Cross‐WLF model. It uses a combined rheological technique using both dynamic and capillary rheometers. Three grades of polycarbonate homopolymers were studied in this work and their complex viscosities were measured using a dynamic shear rheometer. The dynamic data were used to obtain six out of the seven parameters of the Cross‐WLF, except D3. A capillary rheometer fitted with a counter pressure chamber was further used to characterize the pressure dependence of the zero shear viscosity and to determine the D3 parameter. Finally, the derived parameters were validated by carrying out injection molding with a box tool and comparing the actual pressure profiles with simulation results using the Autodesk® MoldFlow® software. The validation results indicated that actual pressure profiles from the simulation were found to be less than 10% than that of injection molding. POLYM. ENG. SCI., 60:517–523, 2020. © 2019 Society of Plastics Engineers

Experimental Characterization and Simulation of Thermoplastic Polymer Flow Hesitation in Thin-Wall Injection Molding Using Direct In-Mold Visualization Technique

“…For example, the viscosity pressure dependency D3 factor was not characterized and considered in the material modeling. As recently investigated by Raha et al [24] in the case of injection-molded polycarbonate material, an accurate D3 factor characterization can reduce injection pressure underestimation errors down to 10% or less. The enlargement of the section in S1 creates a jetting effect that is not correctly represented in the simulation.…”

Injection molding and shear‐induced stress simulation of poly (styrene‐ethylene‐butylene‐styrene) and polypropylene blends

“…Filling simulation needs to know the viscosity of the polymer melt at different temperatures and shear rates 35 . The Cross‐WLF viscosity model can reflect the flow characteristics of the melt in a wide range of shear rates, have a wide temperature adaptability, and can calculate the viscosity of the polymer melt under any conditions 36 . By using algorithms such as least square method 37 and finite difference method, 38 the experimental data of the polymer melt can be fitted to the Cross‐WLF model, the parameters of the rheological model can be determined, and then Moldflow can be used for injection simulation.…”

“…35 The Cross-WLF viscosity model can reflect the flow characteristics of the melt in a wide range of shear rates, have a wide temperature adaptability, and can calculate the viscosity of the polymer melt under any conditions. 36 By using algorithms such as least square method 37 and finite difference method, 38 the experimental data of the polymer melt can be fitted to the Cross-WLF model, the parameters of the rheological model can be determined, and then Moldflow can be used for injection simulation. Ju arez et al 39 used two commercial SEBS mixtures to fit the Cross-WLF model according to the shear viscosity curve, simulated their injection filling characteristics, and verified the accuracy through experiments.…”

Calibration of cavity pressure simulation using autoencoder and multilayer perceptron neural networks

“…For pressure‐sensitive materials, if is missing or the evaluation is inaccurate, large gaps are often found between the pressure predictions of the CAE molding simulation and the actual injection molding pressure observed by the molding operator, resulting in incorrect injection molding machine selection or erroneous mold design. [ 10 ]…”