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The main objective of this paper is to numerically investigate the use of fiber-dependent viscosity models in injection molding simulations of short fiber reinforced thermoplastics with latest commercial software. We propose to use the homogenization-based anisotropic rheological model to take into account flow-fiber coupling effects. The 4th-order viscosity tensor is approximated by an optimal scalar model and then implemented in the Moldflow Insight API framework. Numerical simulations are performed for a test-case rectangular plate with three fiber orientation models. The resulting coupled flow kinematics and fiber evolutions are then compared to the standard uncoupled simulations. Interpretations are given based on detailed post-processing of the field results. Certain deformation conditions are expected to be better taken into account, which may also in return lead to an improved fiber orientation prediction. Preliminary confrontation between flow-fiber coupled simulations and existing experimental data is then presented at the end of the paper.

In this paper, we propose a novel systematic procedure to minimize the discrepancy between the numerically predicted and the experimentally measured fiber orientation results on an injection-molded part. Fiber orientation model parameters are optimized simultaneously using Latin hypercube sampling and kriging-based adaptive surrogate modeling techniques. Via an adequate discrepancy measure, the optimized solution possesses correct skin–shell–core structure and global orientation evolution throughout the considered center-gated disk. Some non-trivial interaction between these parameters and flow-fiber coupling effects as well as their quantitative importance are illustrated. The parametric fine-tuning of orientation models mostly leads to a better agreement in the skin and shell regions, while the coupling effect via a fiber-dependent viscosity improves prediction in the core.