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Remarkable simplicity in the prediction of nonspherical particle segregation

Ryan P. Jones, Julio M. Ottino, Paul B. Umbanhowar, and Richard M. Lueptow
Phys. Rev. Research 2, 042021(R) – Published 28 October 2020

Abstract

Size-disperse mixtures of noncohesive particles segregate, or demix, during flow. For spherical particles, mixture segregation can be predicted based on the relative particle diameters. However, most particle systems in industry and geophysics involve nonspherical particles. Accounting for the immense range of particle shapes introduces additional parameters. As a proxy for nonspherical particles in general, we perform discrete element method simulations of gravity-driven free-surface flows of bidisperse mixtures of mm-sized particles that vary widely in their size and shape (disks, rods, and spheres). Remarkably, the propensity to segregate, measured in terms of a segregation length scale that characterizes the segregation velocity of the two species, can be predicted based on only the volume ratio of the two particle species. The segregation length scale increases linearly with the log of the volume ratio, as it does for bidisperse mixtures of spherical particles, independent of particle shape.

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  • Received 30 June 2020
  • Accepted 13 October 2020

DOI:https://doi.org/10.1103/PhysRevResearch.2.042021

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Polymers & Soft MatterFluid DynamicsInterdisciplinary Physics

Authors & Affiliations

Ryan P. Jones1, Julio M. Ottino1,2,3, Paul B. Umbanhowar1, and Richard M. Lueptow1,2,3,*

  • 1Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, USA
  • 2Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, USA
  • 3The Northwestern Institute on Complex Systems (NICO), Northwestern University, Evanston, Illinois 60208, USA

  • *r-lueptow@northwestern.edu

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Vol. 2, Iss. 4 — October - December 2020

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