Abstract

Predicting the fiber orientation of reinforced molded components is required to improve their performance and safety. Continuum-based models for fiber orientation are computationally very efficient; however, they lack in a linked theory between fiber attrition, fiber–matrix separation and fiber alignment. This work, therefore, employs a particle level simulation which was used to simulate the fiber orientation evolution within a sliding plate rheometer. In the model, each fiber is accounted for and represented as a chain of linked rigid segments. Fibers experience hydrodynamic forces, elastic forces, and interaction forces. To validate this fundamental modeling approach, injection and compression molded reinforced polypropylene samples were subjected to a simple shear flow using a sliding plate rheometer. Microcomputed tomography was used to measure the orientation tensor up to 60 shear strain units. The fully characterized microstructure at zero shear strain was used to reproduce the initial conditions in the particle level simulation. Fibers were placed in a periodic boundary cell, and an idealized simple shear flow field was applied. The model showed a faster orientation evolution at the start of the shearing process. However, agreement with the steady-state aligned orientation for compression molded samples was found.

Highlights

  • Over the past decade, the use of long fiber-reinforced thermoplastics (LFTs) has gained wide acceptance in the automotive industry in order to meet the increasingly tightened corporate average fuel efficiency standards [1,2]

  • A Particle level simulations (PLS) was used to simulate the fiber orientation (FO) evolution of glass fiber-reinforced PP plates sheared in a Sliding Plate Rheometer (SPR)

  • The PLS results showed a faster orientation evolution at the beginning of the shearing process compared to the experimental data

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Summary

Introduction

The use of long fiber-reinforced thermoplastics (LFTs) has gained wide acceptance in the automotive industry in order to meet the increasingly tightened corporate average fuel efficiency standards [1,2]. Continuum-based models for fiber orientation [11,12,13,14], length distribution [15,16], and fiber content prediction [17,18,19] have been developed in the last decades These models employ a probabilistic approach to obtain the fiber configuration evolution during processing which is based on the input parameters, such as fiber characteristics and flow conditions. These models are computationally very efficient and have been implemented into commercial software. Results from both simulation and experiment are presented in this work

Direct Fiber Model
Sample Preparation
Measurement of Fiber Microstructure
Simulation
Conclusions and Outlook
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