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Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy

In the research field of river dynamics, the thickness of bed-load is an important parameter in determining sediment discharge in open channels. Some studies have estimated the bed-load thickness from theoretical and/or experimental perspectives. This study attempts to propose the mathematical formu...

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Autores principales: Zhu, Zhongfan, Yu, Jingshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514612/
https://www.ncbi.nlm.nih.gov/pubmed/33266839
http://dx.doi.org/10.3390/e21020123
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author Zhu, Zhongfan
Yu, Jingshan
author_facet Zhu, Zhongfan
Yu, Jingshan
author_sort Zhu, Zhongfan
collection PubMed
description In the research field of river dynamics, the thickness of bed-load is an important parameter in determining sediment discharge in open channels. Some studies have estimated the bed-load thickness from theoretical and/or experimental perspectives. This study attempts to propose the mathematical formula for the bed-load thickness by using the Tsallis entropy theory. Assuming the bed-load thickness is a random variable and using the method for the maximization of the entropy function, the present study derives an explicit expression for the thickness of the bed-load layer as a function with non-dimensional shear stress, by adopting a hypothesis regarding the cumulative distribution function of the bed-load thickness. This expression is verified against six experimental datasets and are also compared with existing deterministic models and the Shannon entropy-based expression. It has been found that there is good agreement between the derived expression and the experimental data, and the derived expression has a better fitting accuracy than some existing deterministic models. It has been also found that the derived Tsallis entropy-based expression has a comparable prediction ability for experimental data to the Shannon entropy-based expression. Finally, the impacts of the mass density of the particle and particle diameter on the bed-load thickness in open channels are also discussed based on this derived expression.
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spelling pubmed-75146122020-11-09 Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy Zhu, Zhongfan Yu, Jingshan Entropy (Basel) Article In the research field of river dynamics, the thickness of bed-load is an important parameter in determining sediment discharge in open channels. Some studies have estimated the bed-load thickness from theoretical and/or experimental perspectives. This study attempts to propose the mathematical formula for the bed-load thickness by using the Tsallis entropy theory. Assuming the bed-load thickness is a random variable and using the method for the maximization of the entropy function, the present study derives an explicit expression for the thickness of the bed-load layer as a function with non-dimensional shear stress, by adopting a hypothesis regarding the cumulative distribution function of the bed-load thickness. This expression is verified against six experimental datasets and are also compared with existing deterministic models and the Shannon entropy-based expression. It has been found that there is good agreement between the derived expression and the experimental data, and the derived expression has a better fitting accuracy than some existing deterministic models. It has been also found that the derived Tsallis entropy-based expression has a comparable prediction ability for experimental data to the Shannon entropy-based expression. Finally, the impacts of the mass density of the particle and particle diameter on the bed-load thickness in open channels are also discussed based on this derived expression. MDPI 2019-01-29 /pmc/articles/PMC7514612/ /pubmed/33266839 http://dx.doi.org/10.3390/e21020123 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhu, Zhongfan
Yu, Jingshan
Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title_full Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title_fullStr Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title_full_unstemmed Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title_short Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy
title_sort estimating the bed-load layer thickness in open channels by tsallis entropy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514612/
https://www.ncbi.nlm.nih.gov/pubmed/33266839
http://dx.doi.org/10.3390/e21020123
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