Optical method for measuring the volume fraction of granular media: Application to faced-centered cubic lattices of monodisperse spheres.


Journal

Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019

Informations de publication

Date de publication:
Feb 2020
Historique:
received: 13 11 2019
accepted: 13 02 2020
entrez: 15 3 2020
pubmed: 15 3 2020
medline: 15 3 2020
Statut: ppublish

Résumé

In order to understand the dynamics of granular flows, one must have knowledge about the solid volume fraction. However, its reliable experimental estimation is still a challenging task. Here, we present the application of a stochastic-optical method (SOM) [L. Sarno et al., Granul. Matter 18, 80 (2016)10.1007/s10035-016-0676-3] to an array of spheres arranged according to faced-centered cubic lattices, where spheres' locations are known a priori. The purpose of this study is to test the robustness of the image binarization algorithm, introduced in the SOM for the indirect estimation of the near-wall volume fraction through an optically measurable quantity, defined as two-dimensional volume fraction. A comprehensive range of volume fractions and illumination conditions are numerically and experimentally investigated. The proposed binarization algorithm is found to yield reasonably accurate estimations of the two-dimensional volume fraction with a root-mean-square error smaller than 0.03 for all investigated illumination conditions. A slightly worse performance is observed for samples with relatively low volume fractions (<0.3), where the binarization algorithm occasionally cannot identify the surface elements in the second and third layers of the regular lattice.

Identifiants

pubmed: 32168704
doi: 10.1103/PhysRevE.101.022904
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

022904

Auteurs

L Sarno (L)

Department of Civil Engineering, University of Salerno, 84084 Fisciano, Italy.
Institute of Fluid Dynamics (FDY), Technische Universität Darmstadt, 64287 Darmstadt, Germany.

L Carleo (L)

Department of Civil Engineering, University of Salerno, 84084 Fisciano, Italy.

M N Papa (MN)

Department of Civil Engineering, University of Salerno, 84084 Fisciano, Italy.

A Armanini (A)

Department of Civil, Environmental and Mechanical Engineering, CUDAM, University of Trento, 38123 Trento, Italy.

Classifications MeSH