Optimization of fiber prediction model coefficients in injection molding simulation based on micro computed tomography

Abstract

Fiber‐reinforced thermoplastic for low weight application become increasingly important for many industrial branches. During the injection molding of short fiber‐reinforced thermoplastic parts the fibers become orientated. This orientation is determined on the one hand by the geometry of the part, and on the other hand by the injection molding parameters, and influence the mechanical behavior of the part. The determination of the fiber properties that is, the orientation distribution of the fibers, is therefore of considerable interest. Since a more accurate fiber orientation prediction of the injection molding simulation will lead to a more precise structural simulation the objective of the present work is to achieve a preferably accurate orientation distribution. To describe the orientation distribution of the fibers, the fiber orientation tensor defined by Advani and Tucker (Advani and Tucker, Journal of Rheology, 31, 751 (1987)) was used. To determine the entries of this tensor micro computed tomography scans (μCT‐scans) of an injection‐molded plate, as well as an injection‐molded specimen with different cross section and shape were performed. Injection molding simulation using Autodesk Moldflow Insight were carried out. The residual strain closure (RSC) model was the underlying model to depict the fiber orientation distribution, or rather the orientation tensors. The two model parameters, the fiber interaction coefficient Ci and the scalar factor κ, were adapted by an optimization procedure, in such a way that the orientation distributions of the simulations fit the results of the μCT‐analysis at its best. POLYM. ENG. SCI., 59:E152–E160, 2019. © 2018 Society of Plastics Engineers