A quantitative image analysis method for characterizing mixtures of granular materials

Abstract

Automated image analysis is used to characterize the structure of undisturbed granular mixtures. These mixtures, produced from small-scale mixing experiments, are preserved using solidification techniques, sliced, and scanned using a video camera to produce a digital image. Image analysis is used to determine the mean, mode, standard deviation, variance, and skewness of local composition for a large number of locations in the mixtures, providing an effective method for performing a detailed quantitative characterization of the mixture structure. The digital data are then used to simulate random sampling from a powder blender. Sampling parameters, such as number of samples, sample size, and location of the samples, are varied to assess their effect on the descriptive statistics. For partially mixed systems such as those examined here, results depend strongly on the number of samples used in the analysis, but they are largely independent of sample size. The solidification techniques, image analysis methods, and numerical algorithms for quantifying features of the partially mixed structures are described in detail.