Experimental investigation and numerical modelling of density-driven segregation in an annular shear cell - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Advanced Powder Technology Année : 2021

Experimental investigation and numerical modelling of density-driven segregation in an annular shear cell

Monica Tirapelle
  • Fonction : Auteur
Andrea C Santomaso
  • Fonction : Auteur
  • PersonId : 1097754

Résumé

Granular materials segregate spontaneously due to differences in particle size, shape, density and flow behaviour. In this paper we experimentally investigate density-difference-driven segregation for a range of density ratios and a range of heavy particle concentrations. The experiments are conducted in an annular shear cell with rotating bumpy bottom that yields an exponential shear profile. The cell is initially filled with a layer of light particles and an upper layer of heavier grains and, on top, a load provides confinement. The segregation process is filmed through the transparent side-wall with a camera, and the evolution of particle concentration in space and time is evaluated by means of post-processing image analysis. We also propose a continuum-approach to model density-driven segregation. We use a segregation-diffusion transport equation, constitutive relations for effective viscosity and friction coefficient, and a segregation velocity analogous to the Stokes’ law. The model, which is validated by comparison with experimental findings, can successfully predict density-driven segregation at different density ratios and volumetric fraction.
Fichier principal
Vignette du fichier
manuscript.pdf (6.7 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03215666 , version 1 (03-05-2021)

Identifiants

Citer

Monica Tirapelle, Andrea C Santomaso, Patrick Richard, Riccardo Artoni. Experimental investigation and numerical modelling of density-driven segregation in an annular shear cell. Advanced Powder Technology, 2021, 32 (5), pp.1305-1317. ⟨10.1016/j.apt.2021.02.020⟩. ⟨hal-03215666⟩
21 Consultations
16 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More