Particle near-neighbour separation index for quantification of segregation of granular material

• Published in: Powder technology 2020-01, Vol.360, p.481-492
• Main Authors: Chibwe, Deside Kudzai, Evans, Geoffrey Michael, Doroodchi, Elham, Monaghan, Brian Joseph, Pinson, David John, Chew, Sheng J.
• Format: Article
• Language: English
• Subjects: Discrete element modelling; Granular flow; Granular materials; Homogeneity; Mixing and segregation; Segregation process; Separation; Separation index
• ISSN: 0032-5910; 1873-328X
• DOI: 10.1016/j.powtec.2019.10.079

In this study, an alternative approach named near-neighbour separation index (NNSI) is proposed which defines mixing and segregation in terms of the nearest-neighbour particle scale methodology to characterise the evolution of particle-particle relationships in granular material flow systems so as to inform the extent of mixing and segregation (homogeneity) in space and time. Use is made of the geometrical particle information (position) as a function of time from the DEM simulations data to provide an instantaneous description and evaluation of the mixing and segregation process without due regard of particle history and initial configuration. The NNSI was found to give useful inferences on segregation and dispersion as it provides an unprecedented quantification of the particle-particle scale distributions of particles and fully provides a quantitative description of the particle mixture homogeneity. Furthermore, the NNSI is quite promising with added advantage and capability of handling discrete multi-size particle systems. [Display omitted] •DEM particle spatial positions was used to describe granular material segregation.•Near neighbour separation index developed captures the dispersion characteristics.•Computed index is dependent on number distribution of particles and energy input.