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| Titel |
Capturing 2D transient surface data of granular flows against obstacles with an RGB-D sensor |
| VerfasserIn |
Daniel Caviedes-Voullième, Carmelo Juez, Javier Murillo, Pilar Garcia-Navarro |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250095198
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| Publikation (Nr.) |
 EGU/EGU2014-10649.pdf |
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| Zusammenfassung |
| Landslides are an ubiquitous natural hazard, and therefore human infrastructure and
settlements are often at risk in mountainous regions. In order to better understand and predict
landslides, systematic studies of the phenomena need to be undertaken. In particular,
computational tools which allow for analysis of field problems require to be thoroughly
tested, calibrated and validated under controlled conditions. And to do so, it is necessary for
such controlled experiments to be fully characterized in the same terms as the numerical
model requires. This work presents an experimental study of dry granular flow over a rough
bed with topography which resembles a mountain valley. It has an upper region with a very
high slope. The geometry of the bed describes a fourth order polynomial curve, with a low
point with zero slope, and afterwards a short region with adverse slope. Obstacles
are present in the lower regions which are used as model geometries of human
structures. The experiments consisted of a sudden release a mass of sand on the upper
region, and allowing it to flow downslope. Furthermore, it has been frequent in
previous studies to measure final states of the granular mass at rest, but seldom
has transient data being provided, and never for the entire field. In this work we
present transient measurements of the moving granular surfaces, obtained with a
consumer-grade RGB-D sensor. The sensor, developed for the videogame industry, allows
to measure the moving surface of the sand, thus obtaining elevation fields. The
experimental results are very consistent and repeatable. The measured surfaces clearly
show the distinctive features of the granular flow around the obstacles and allow to
qualitatively describe the different flow patterns. More importantly, the quantitative
description of the granular surface allows for benchmarking and calibration of predictive
numerical models, key in scaling the small-scale experimental knowledge into the field. |
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