Digital sieving of irregular 3D particles - A study using XRCT and statistically similar synthetic data

The properties of particulate materials are influenced by purely geometric properties like size, size distribution, and shape. However, size is an ambiguous quantity for non-spherical particles. Therefore, the impact of particle shape on the size as measured by several common and original estimators is investigated. Particularly, a high-fidelity digital sieving method based on the first principal axis of a particle is proposed. An XRCT scan of asphalt concrete is analysed for the shape distribution and its compliance with typical standards. Then, a larger synthetic particle set with a statistically similar, but slightly more extreme shape distribution is generated for testing the size estimators. It is found that the equivalent volume sphere should be abandoned and alternatives are proposed. The analysis is based on simple discrete computational geometry and can easily be implemented.