Assessment of internal fabric of particulate materials

This paper presents two powerful techniques for evaluating the internal fabric of particulate materials. The first technique, named Voronoi tessellation, offers several improvements over existing methods by adopting a new polygon generation criterion. It was implemented in an application-oriented image analysis and recognition algorithm capable of generating Voronoi polygons, and calculating the local void ratio of particle groups from microscopic images. Verification calculations included performing digitization of a synthetic image using Oda’s and Voronoi tessellation methods. It has been found that Voronoi tessellation has the advantage compared to Oda’s method, because it has a well-defined polygon generation criterion whereas Oda’s method is highly dependent on the operator-chosen polygon system. The internal fabric of sand specimens was also investigated using Computed Tomography (CT) that capable of detecting material density variation. The CT technique demonstrated good ability to detect specimen inhomogeneities, localization patterns, and quantifying void ratio variation within sand specimens.