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Construction of poly-ellipsoidal grain shapes from SMT imaging on sand, and the development of a new DEM contact detection algorithm

Boning Zhang, Richard Regueiro, Andrew Druckrey, Khalid Alshibli

Engineering Computations

ISSN: 0264-4401

Article publication date: 16 April 2018

272

Abstract

Purpose

This paper aims to construct smooth poly-ellipsoid shapes from synchrotron microcomputed tomography (SMT) images on sand and to develop a new discrete element method (DEM) contact detection algorithm.

Design/methodology/approach

Voxelated images generated by SMT on Colorado Mason sand are processed to construct smooth poly-ellipsoidal particle approximations. For DEM contact detection, cuboidal shape approximations to the poly-ellipsoids are used to speed up contact detection.

Findings

The poly-ellipsoid particle shape approximation to Colorado Mason sand grains is better than a simpler ellipsoidal approximation. The new DEM contact algorithm leads to significant speedup and accuracy is maintained.

Research limitations/implications

The paper limits particle shape approximation to smooth poly-ellipsoids.

Practical implications

Poly-ellipsoids provide asymmetry of particle shapes as compared to ellipsoids, thus allowing closer representation of real sand grain shapes that may be angular and unsymmetric. When incorporated in a DEM for computation, the poly-ellipsoids allow better representation of particle rolling, sliding and interlocking phenomena.

Originality/value

Method to construct poly-ellipsoid particle shapes from SMT data on real sands and computationally efficient DEM contact detection algorithm for poly-ellipsoids.

Keywords

Acknowledgements

Funding for this research was provided by ONR MURI grant N00014-11-1-0691. This funding is gratefully acknowledged.

Citation

Zhang, B., Regueiro, R., Druckrey, A. and Alshibli, K. (2018), "Construction of poly-ellipsoidal grain shapes from SMT imaging on sand, and the development of a new DEM contact detection algorithm", Engineering Computations, Vol. 35 No. 2, pp. 733-771. https://doi.org/10.1108/EC-01-2017-0026

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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