Abstract
Short fiber reinforced composites have a variety of micro-structural parameters that affect their macro-mechanical performance. A modeling methodology, capable of accommodating a broad range of these parameters, is desirable. This paper describes a micro-mechanical model which is developed using Finite Element Analysis and Orientation Averaging. The model is applicable to short fiber reinforced composites with a wide variety of micro-structural parameters such as arbitrary fiber volume fractions, fiber aspect ratios and fiber orientation distributions. In addition to the Voigt and Reuss assumptions, an interaction model is developed based on the self-consistent assumption. Comparisons with experimental results, and direct numerical simulations of Representative Volume Elements show the capability of the model for fair predictions.
Highlights
Short Fiber Reinforced Composites (SFRCs) are becoming more and more interesting for different industries due to their high strength-todensity and stiffness-to-density ratios in comparison to unreinforced polymers
A micro-mechanical modeling approach which has been frequently used for SFRCs is computational homogenization
A numerical Representative Volume Element (RVE) of an SFRC is analyzed by numerical methods and the homogenized material response is obtained by volume averaging
Summary
Short Fiber Reinforced Composites (SFRCs) are becoming more and more interesting for different industries due to their high strength-todensity and stiffness-to-density ratios in comparison to unreinforced polymers. A numerical Representative Volume Element (RVE) of an SFRC is analyzed by numerical methods (most often by the Finite Element Method) and the homogenized material response is obtained by volume averaging This modeling approach has a very strong predictive capability. Comparisons to computational homogenization an alyses on realistic RVEs (performed in this study) show that for some cases, the self-consistent model provides a more accurate prediction of the composite stiffness properties than the Voigt and Reuss models. The presented method in this paper is applicable to almost any SFRC, with any desired fiber aspect ratio, fiber volume fraction and fiber orientation distribution This is an important advantage over computational ho mogenization, since RVE generation is, for some cases, very challenging.
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