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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-7514612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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