Modeling heterogeneous materials via two-point correlation functions. II. Algorithmic details and applications

Type: Article

Publication Date: 2008-03-27

Citations: 265

DOI: https://doi.org/10.1103/physreve.77.031135

Abstract

In the first part of this series of two papers, we proposed a theoretical formalism that enables one to model and categorize heterogeneous materials (media) via two-point correlation functions ${S}_{2}$ and introduced an efficient heterogeneous-medium (re)construction algorithm called the ``lattice-point'' algorithm. Here we discuss the algorithmic details of the lattice-point procedure and an algorithm modification using surface optimization to further speed up the (re)construction process. The importance of the error tolerance, which indicates to what accuracy the media are (re)constructed, is also emphasized and discussed. We apply the algorithm to generate three-dimensional digitized realizations of a Fontainebleau sandstone and a boron-carbide/aluminum composite from the two-dimensional tomographic images of their slices through the materials. To ascertain whether the information contained in ${S}_{2}$ is sufficient to capture the salient structural features, we compute the two-point cluster functions of the media, which are superior signatures of the microstructure because they incorporate topological connectedness information. We also study the reconstruction of a binary laser-speckle pattern in two dimensions, in which the algorithm fails to reproduce the pattern accurately. We conclude that in general reconstructions using ${S}_{2}$ only work well for heterogeneous materials with single-scale structures. However, two-point information via ${S}_{2}$ is not sufficient to accurately model multiscale random media. Moreover, we construct realizations of hypothetical materials with desired structural characteristics obtained by manipulating their two-point correlation functions.

Locations

  • Physical Review E - View
  • arXiv (Cornell University) - View - PDF
  • PubMed - View
  • DataCite API - View

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