Analyzing X-ray tomographies of granular packings

Area of Science:

• Physics
• Materials Science
• Computational Science

Background:

• Granular materials are ubiquitous in nature and industry.
• Understanding their structure is crucial for predicting bulk properties.
• 3D imaging techniques like X-ray Computed Tomography offer detailed insights into granular packings.

Purpose of the Study:

• To develop and present methods for analyzing particle properties within 3D granular packing data.
• To provide a comprehensive analysis including particle detection, Voronoi cell characterization, and contact network analysis.
• To offer a freely available software package for reproducing and extending the analysis.

Main Methods:

• Utilizing 3D volume data, primarily from X-ray Computed Tomography.
• Implementing algorithms for individual particle detection within the packing.
• Calculating pair correlation functions, Voronoi cell properties (volume, shape), and inter-particle contact information.

Main Results:

• Successful detection and property analysis of particles in monodisperse sphere packings.
• Extension of methods to analyze packings of ellipsoids and tetrahedra.
• Demonstration of comprehensive analysis including structural and topological properties.

Conclusions:

• The presented methods provide a robust framework for granular packing analysis.
• The accompanying software facilitates reproducible research and further development in granular material science.
• This work enhances the understanding of structure-property relationships in granular systems.