FCA method for predicting effective viscosity of particle reinforced thermoplastic melt and a metric for measuring clusters

Abstract

The effective viscosity of particle reinforced thermoplastic melt shows strongly anisotropic behavior and is also shear rate-dependent. The traditional homogenization method may face challenge due to extremely expensive computational cost, when the non-linear effective viscosities on all the directions of Particle Reinforced Thermoplastics (PRT) are demanded. This paper approaches this challenge with the FEM-Cluster based reduced order Analysis (FCA) method [1]. The governing equations are solved by minimizing a cluster-based dual formulation of the dissipating energy, where the cluster-wise Admissible Shear Stress (ASS) set is obtained by FCA together with a Spectrum Analysis Algorithm (SAA). In addition, considering the fact that there is a lack of effective method for determining the proper number of clusters, a cluster metric is developed, which relates the given number of clusters and the prediction accuracy of FCA method. This metric can be easily used in the offline stage to pre-estimate the applicability of the obtained clusters on the given loading conditions with a small amount of additional computation.