Surface orientation tensor to predict preferred contact orientation and characterise the form of individual particles

Ákos Orosz, Vasileios Angelidakis, Katalin Bagi

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)
16 Downloads (Pure)

Abstract

The characterisation and classification of particle form are typically based on the consideration of the main particle dimensions, for the derivation of which no method has been unanimously accepted or proven to be representative of its morphology or load-bearing capabilities. This study proposes a weighted fabric tensor, named “surface orientation tensor”, that characterises the form of an individual particle. Using the eigenvalues of this tensor, efficient measures of compactness, flakiness and elongation are proposed. In comparison to the traditional oriented bounding box approaches, it has the advantage that it is based directly on the orientations of the normal vectors of the faces forming the surface of the particle, i.e. those directions along which the particle can best transmit contact forces to its neighbours. The advantages of the proposed approach are pointed out with discrete element simulations on assemblies of polyhedral particles.

Original languageEnglish
Pages (from-to)312-325
Number of pages14
JournalPowder Technology
Volume394
Early online date25 Aug 2021
DOIs
Publication statusPublished - 01 Dec 2021
Externally publishedYes

Keywords

  • DEM
  • Fabric tensor
  • Grain morphology
  • Railway ballast
  • Surface orientation tensor

ASJC Scopus subject areas

  • General Chemical Engineering

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