Evaluation of the Predictive Power of 2D Particle Imaging for 3D Characteristics in Bulk Material Analysis

Abstract

Particle size and shape characteristics are commonly measured with twodimensional (2D) imaging techniques, two of which are static or dynamic imaging techniques. These 2D particle characteristics need to be applied to particulate processes where they model three-dimensional (3D) processes. The correlation between 2D and 3D particle characteristics is therefore necessary, but the knowledge is still limited to either mathematically simple shapes or a certain set of investigated bulk solids. A particle dataset consisting of six bulk solids measured with X-ray microscopy was used to simulate the results of 2D imaging techniques to create a database to test the correlation between sets of particle characteristics. The dataset thus created offers the possibility to study the correlation between characteristic values and robustly predict the 3D properties of bulk solids measured with 2D measurement techniques. It is found that the form factor, the square of circularity, is a good predictor of Wadell’s sphericity, while the correlation can be improved by including additional 2D characteristics, namely convexity and the ratio of bounding circles.