Eigenparticles: characterizing particles using eigenfaces

Higham, J. E.; Vaidheeswaran, A.; Benavides, K.; Shepley, P.

doi:10.1007/s10035-019-0900-z

Title: Eigenparticles: characterizing particles using eigenfaces

Journal Article · 23 May 2019 · Granular Matter

DOI: https://doi.org/10.1007/s10035-019-0900-z · OSTI ID:1582388

^[1]; Vaidheeswaran, A. ^[2]; Benavides, K. ^[2]; Shepley, P. ^[3]

Univ. of Liverpool (United Kingdom)
National Energy Technology Lab. (NETL), Morgantown, WV (United States)
Univ. of Sheffield (United Kingdom)

The shape characteristics of particles have a pinnacle role in microsopic and macroscopic features of a system. Several studies have highlighted the need for considering deviations from a spherical representation of particles for accurate modeling of granular and multiphase flow systems. Using a shape factor, sphericity or roundness parameter alone is proven to be inadequate to capture the physical phenomena. In the present study we propose a novel metric based on the pattern recognition method Eigenfaces, coining the technique ‘Eigenparticles’. Using this technique we create a single statistical distribution of basis shapes to describe the morphological composition. The proposed technique is successfully validated with test shapes and applied to real particles. As a result, when compared with a state-of-the-art Fourier based method, ‘Eigenparticles’ performs favorably, clearly distinguishing the different particles.

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Research Organization:: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE)

OSTI ID:: 1582388

Journal Information:: Granular Matter, Vol. 21, Issue 3; ISSN 1434-5021

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 4 works

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