Identification of avalanche precursors by acoustic probing in the bulk of tilted granular layers
Author(s) -
M Duranteau,
Vincent Tournat,
V. I. Zaĭtsev,
Renaud Delannay,
Patrick Richard
Publication year - 2013
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.177
H-Index - 75
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.4812015
Subject(s) - granular material , relaxation (psychology) , millisecond , acoustic emission , nonlinear system , materials science , acoustic wave , granular matter , tracking (education) , mechanics , acoustics , physics , composite material , psychology , social psychology , pedagogy , quantum mechanics , astronomy
International audienceUnderstanding the precursors of granular avalanches is important for the prediction of critical events. As part of the dynamics leading to the avalanche, precursors are identified as collective motions of grains on the free surface. When a granular pile is tilted at a constant angular velocity, precursors appear quasi-periodically. In this paper we simultaneously caracterize precursors on the free surface with an optical method and in the bulk with acoustic methods (nonlinear and linear). Surprisingly, the use on nonlinear acoustic method is not necessary to probe rearrangements in the bulk of the granular material. A linear method can also be used provided that the frequency region is the one where the acoustic propagation is sensitive to the solid skeleton formed by the bead-contact network. Our experiments conducted with monodisperse glass beads show that their surface features are by far the most important for the precursor propreties. Our results allow to probe with a few millisecond time resolution (less than 10−2 degree of inclination) the relaxation phenomena associated to each precursor event. Interpretations of different precursors and different experiments provide an interesting train of thought for the understanding of destabilization mechanisms in granular systems
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