No abstract

Long fiber-reinforced thermoplastics (LFTs) are an attractive design option for many engineering applications due to their excellent mechanical properties and processability. When processing these materials, the length of the fibers inevitably decreases, which ultimately affects the mechanical performance of the finished part. Since none of the existing modeling techniques can accurately predict fiber damage of LFTs during injection molding, a new phenomenological approach for modeling fiber attrition is presented. First, multiple controlled studies employing a Couette rheometer are performed to determine correlations between processing conditions, material properties, and fiber length reduction. The results show shear stress and fiber concentration impact fiber damage. Based on these findings, a phenomenological model to predict breaking rate and unbreakable length of a fiber under giving conditions is developed. The model is based on the beam theory with distributed hydrodynamic stresses acting on a fiber. Fiber–fiber interactions are accounted for and correlated with the fiber volume fraction via a fitting parameter. The model tracks both the number-average and weight-average fiber length during processing, which can in turn be used to extract the fiber length distribution.

The simulative prediction of fiber orientation for injection-molded short fiber-reinforced thermoplastics is an important step in prediction warpage and failure of injection molded parts. There exists a variety of phenomenological macroscopic fiber orientation models, which are computationally very efficient but strongly dependent on phenomenological parameters. This research focuses on a mechanistic fiber orientation model for concentrated short fiber-reinforced thermoplastics. A fully coupled computational fluid dynamics particle simulation is used to estimate the lubrication forces between two fibers in different configurations (angles between fibers, velocities) with varying fiber length and surrounding fluid viscosity. Based on these data, a calibrated lubrication model is developed and implemented in a mechanistic fiber orientation simulation. In addition, the fiber orientation estimated by the enhanced mechanistic fiber model is compared to experimental fiber orientation data obtained with a glass fiber-reinforced thermoplastic industrial grade, which showed an improvement over a simulation that did not include the lubrication force.