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Particle size and shape characteristics are commonly measured with two-dimensional (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 specific sets 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 dataset 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. Several correlations are determined. These include predictive equations for Wadell’s sphericity (3D) from 2D shape factors and particle width (3D) from Feret diameters (2D). The correlations have been validated with dynamic image analysis measurements. The correlations allow the practitioner in principle to predict particle sphericity and sieve size distribution from dynamic image analysis for compact particles. • Workflow for simulation of static and dynamic image analysis is presented. • Particle characteristics for several solids types are determined. • Influence of image analysis methods on shape factors are shown. • A correlation for 3D sphericity from 2D shape factors is found. • A correlation of particle width from 2D measures is found.
Buchwald et al. (Tue,) studied this question.