Abstract
Pore scale modeling plays a key role in fluid flow through porous media and associated macroscale constitutive relationships. The polyhedral shape and effective local pore size within granular material microstructure are computed in this study by means of the Euclidean Distance Transform (EDT), a local maxima search (non-maximum suppression), and a segmentation process. Various synthetic packed particles are simulated and employed as comparative models during the computation of pore size distribution (PSD). Reconstructed un-sheared and sheared Ottawa 20–30 sand samples are used to compute PSD for non-trivial and non-spherical models.
Highlights
Pore space modeling is a challenging issue for scientists in various disciplines
Insight into the pore space is essential to homogenization techniques and the macroscale constitutive modeling of flow through porous media [1,2,3]
A variety of approaches are available for computing the pore size distribution (PSD) mainly categorized in Delaunay tessellation, medial axis, and watershed based methods [9,10,11,12,13,14,15,16,17,18]
Summary
Pore space modeling is a challenging issue for scientists in various disciplines. Granular structures yield complex pore geometries, not accessible experimentally and difficult to characterize using non-idealized computational methods. A variety of approaches are available for computing the pore size distribution (PSD) mainly categorized in Delaunay tessellation, medial axis, and watershed based methods [9,10,11,12,13,14,15,16,17,18]. A new adaptive method is proposed to discretize the pore space and compute the PSD consistent with a diverse range of void shapes and unrestrained by the need of user-defined parameters. A segmentation process (minimum Euclidean distance assignment) [24] is applied to discriminate individual pores, irrespective of shape or size, in the originally continuous void space. The soundness of the PSD characterization technique described in this paper is demonstrated through its application to 3D digital models of Ottawa 20–30 sand specimens [32,33]
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