Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/79517
Title: Visual analysis of density and velocity profiles in dense 3D granular gases
Author(s): Puzyrev, Dmitry
Fischer, David
Harth, Kirsten
Trittel, TorstenLook up in the Integrated Authority File of the German National Library
Hidalgo, Raúl Cruz
Falcon, Eric
Noirhomme, Martial
Opsomer, Eric
Vandewalle, Nicolas
Garrabos, Yves
Lecoutre, Carole
Palencia, Fabien
Stannarius, Ralf
Issue Date: 2021
Type: Article
Language: English
URN: urn:nbn:de:gbv:ma9:1-1981185920-814713
Subjects: Visual analysis
Density
Velocity profiles
Granular gases
Abstract: Granular multiparticle ensembles are of interest from fundamental statistical viewpoints as well as for the understanding of collective processes in industry and in nature. Extraction of physical data from optical observations of three-dimensional (3D) granular ensembles poses considerable problems. Particle-based tracking is possible only at low volume fractions, not in clusters. We apply shadowbased and feature-tracking methods to analyze the dynamics of granular gases in a container with vibrating side walls under microgravity. In order to validate the reliability of these optical analysis methods, we perform numerical simulations of ensembles similar to the experiment. The simulation output is graphically rendered to mimic the experimentally obtained images. We validate the output of the optical analysis methods on the basis of this ground truth information. This approach provides insight in two interconnected problems: the confirmation of the accuracy of the simulations and the test of the applicability of the visual analysis. The proposed approach can be used for further investigations of dynamical properties of such media, including the granular Leidenfrost effect, granular cooling, and gas-clustering transitions.
URI: https://opendata.uni-halle.de//handle/1981185920/81471
http://dx.doi.org/10.25673/79517
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Sponsor/Funder: OVGU-Publikationsfonds 2021
Journal Title: Scientific reports
Publisher: Macmillan Publishers Limited, part of Springer Nature
Publisher Place: [London]
Volume: 11
Issue: 2021
Original Publication: 10.1038/s41598-021-89949-z
Page Start: 1
Page End: 12
Appears in Collections:Fakultät für Naturwissenschaften (OA)

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