Microstructure-based modeling of anisotropic behavior of additively manufactured short glass fiber reinforced polypropylene
Topic(s) : Manufacturing
Co-authors :
Martin REITER (AUSTRIA), Anna HOESSINGER-KALTEIS , Michael JERABEK (AUSTRIA), Simon GASTL (AUSTRIA), Dietmar SALABERGER , Zoltan MAJORAbstract :
Short glass fiber (SGF) reinforced polymers play a crucial role in the production of high-performance components, especially through additive manufacturing methods that allow for optimized fiber orientation within each layer. This study focuses on the microstructure-based modeling of anisotropic behavior in extrusion-based additively manufactured SGF-polypropylene (PP).
In the initial phase, filaments of an automotive-grade SGF-PP were produced, and optimal printing conditions were meticulously identified. The study emphasizes the need to predict proper fiber orientation-dependent material behavior for designing load path-optimized components. To address this, a mean field homogenization (MFH) material model was chosen due to its ability to integrate complex fiber orientation, matrix behavior, and fiber properties efficiently. The MFH model offers a computationally efficient prediction of the mechanical response and can be seamlessly integrated into finite element (FEM) simulations for complex components.
The calibration process involved the production and testing of a range of unidirectional (UD) specimens with printing orientations ranging from 0° to 90°. Considering the complex nature of fiber orientations within printed strands, a second order fiber orientation tensor (FOT) was employed to describe these in-strand orientations. The FOT was identified through reverse engineering using all UD specimens and directly measured using CT imaging. Both approaches yielded consistent results. The PP matrix properties that are a necessity for the MFH model were provided by the material supplier. In addition, these properties were also identified using a reverse engineering approach on the UD-specimens. Thus, the MFH model could be successfully calibrated using the printed UD-specimens and the measured or reverse-engineered FOT. To validate the MFH model for various geometries and print orientations, it was integrated into a finite element simulation and the mechanical properties of cross-ply tensile specimens and complex components were computed and compared to mechanical tests. This comprehensive approach revealed a good agreement between the simulation and testing.
This study significantly advances our understanding of SGF-PP in additive manufacturing, specifically by addressing complex fiber orientations within printed strands and their influence on predicting the mechanical properties of printed components. The combined MFH FEM model can further integrate into optimization algorithms, enabling geometry and path planning optimization in the realm of high-performance component production.
In the initial phase, filaments of an automotive-grade SGF-PP were produced, and optimal printing conditions were meticulously identified. The study emphasizes the need to predict proper fiber orientation-dependent material behavior for designing load path-optimized components. To address this, a mean field homogenization (MFH) material model was chosen due to its ability to integrate complex fiber orientation, matrix behavior, and fiber properties efficiently. The MFH model offers a computationally efficient prediction of the mechanical response and can be seamlessly integrated into finite element (FEM) simulations for complex components.
The calibration process involved the production and testing of a range of unidirectional (UD) specimens with printing orientations ranging from 0° to 90°. Considering the complex nature of fiber orientations within printed strands, a second order fiber orientation tensor (FOT) was employed to describe these in-strand orientations. The FOT was identified through reverse engineering using all UD specimens and directly measured using CT imaging. Both approaches yielded consistent results. The PP matrix properties that are a necessity for the MFH model were provided by the material supplier. In addition, these properties were also identified using a reverse engineering approach on the UD-specimens. Thus, the MFH model could be successfully calibrated using the printed UD-specimens and the measured or reverse-engineered FOT. To validate the MFH model for various geometries and print orientations, it was integrated into a finite element simulation and the mechanical properties of cross-ply tensile specimens and complex components were computed and compared to mechanical tests. This comprehensive approach revealed a good agreement between the simulation and testing.
This study significantly advances our understanding of SGF-PP in additive manufacturing, specifically by addressing complex fiber orientations within printed strands and their influence on predicting the mechanical properties of printed components. The combined MFH FEM model can further integrate into optimization algorithms, enabling geometry and path planning optimization in the realm of high-performance component production.