Abstract
Statistical continuum theory is a powerful tool for predicting the effective properties of heterogeneous materials, where the shape of the fillers is random over the representative volume element (RVE). Due to this geometrical complexity of the shape of fillers, the heterogeneous material might present some anisotropy, which can be difficult to measure experimentally. In these cases the statistical continuum theory can be used as a tool to predict the degree of anisotropy. The aim of the present work is to present an implementation method based on analytical probability functions that can be easily integrated numerically to predict the effective properties of heterogeneous materials. In this regard, the strong-contrast version of the statistical continuum theory is used to predict the effective mechanical properties of heterogeneous materials. For validation, the effective mechanical properties of porous P-311 glass are predicted using the strong-contrast approach, and compared to experimental results and to ones calculated using a differential scheme (DS) model, which is based on Eshelby’s theory of inclusion embedded in an equivalent continuum matrix. Further, to demonstrate the effectiveness of the strong-contrast approach in dealing with anisotropic materials, the effective mechanical properties of a macroscopically anisotropic heterogeneous material are predicted and compared to ones calculated using the DS model. Finally, remarks on the implementation of the strong-contrast approach are highlighted through calculations using fillers with different sizes.
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