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Image-based Lagrangian Particle Tracking in Bed-load Experiments
Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sedimen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MyJove Corporation
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5612569/ https://www.ncbi.nlm.nih.gov/pubmed/28784943 http://dx.doi.org/10.3791/55874 |
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author | Radice, Alessio Sarkar, Sankar Ballio, Francesco |
author_facet | Radice, Alessio Sarkar, Sankar Ballio, Francesco |
author_sort | Radice, Alessio |
collection | PubMed |
description | Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two action-cameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol. |
format | Online Article Text |
id | pubmed-5612569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MyJove Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-56125692017-10-10 Image-based Lagrangian Particle Tracking in Bed-load Experiments Radice, Alessio Sarkar, Sankar Ballio, Francesco J Vis Exp Environmental Sciences Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two action-cameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol. MyJove Corporation 2017-07-20 /pmc/articles/PMC5612569/ /pubmed/28784943 http://dx.doi.org/10.3791/55874 Text en Copyright © 2017, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Environmental Sciences Radice, Alessio Sarkar, Sankar Ballio, Francesco Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title | Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title_full | Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title_fullStr | Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title_full_unstemmed | Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title_short | Image-based Lagrangian Particle Tracking in Bed-load Experiments |
title_sort | image-based lagrangian particle tracking in bed-load experiments |
topic | Environmental Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5612569/ https://www.ncbi.nlm.nih.gov/pubmed/28784943 http://dx.doi.org/10.3791/55874 |
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