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Intelligent Flow Friction Estimation
Nowadays, the Colebrook equation is used as a mostly accepted relation for the calculation of fluid flow friction factor. However, the Colebrook equation is implicit with respect to the friction factor (λ). In the present study, a noniterative approach using Artificial Neural Network (ANN) was devel...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834174/ https://www.ncbi.nlm.nih.gov/pubmed/27127498 http://dx.doi.org/10.1155/2016/5242596 |
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author | Brkić, Dejan Ćojbašić, Žarko |
author_facet | Brkić, Dejan Ćojbašić, Žarko |
author_sort | Brkić, Dejan |
collection | PubMed |
description | Nowadays, the Colebrook equation is used as a mostly accepted relation for the calculation of fluid flow friction factor. However, the Colebrook equation is implicit with respect to the friction factor (λ). In the present study, a noniterative approach using Artificial Neural Network (ANN) was developed to calculate the friction factor. To configure the ANN model, the input parameters of the Reynolds Number (Re) and the relative roughness of pipe (ε/D) were transformed to logarithmic scales. The 90,000 sets of data were fed to the ANN model involving three layers: input, hidden, and output layers with, 2, 50, and 1 neurons, respectively. This configuration was capable of predicting the values of friction factor in the Colebrook equation for any given values of the Reynolds number (Re) and the relative roughness (ε/D) ranging between 5000 and 10(8) and between 10(−7) and 0.1, respectively. The proposed ANN demonstrates the relative error up to 0.07% which had the high accuracy compared with the vast majority of the precise explicit approximations of the Colebrook equation. |
format | Online Article Text |
id | pubmed-4834174 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-48341742016-04-28 Intelligent Flow Friction Estimation Brkić, Dejan Ćojbašić, Žarko Comput Intell Neurosci Research Article Nowadays, the Colebrook equation is used as a mostly accepted relation for the calculation of fluid flow friction factor. However, the Colebrook equation is implicit with respect to the friction factor (λ). In the present study, a noniterative approach using Artificial Neural Network (ANN) was developed to calculate the friction factor. To configure the ANN model, the input parameters of the Reynolds Number (Re) and the relative roughness of pipe (ε/D) were transformed to logarithmic scales. The 90,000 sets of data were fed to the ANN model involving three layers: input, hidden, and output layers with, 2, 50, and 1 neurons, respectively. This configuration was capable of predicting the values of friction factor in the Colebrook equation for any given values of the Reynolds number (Re) and the relative roughness (ε/D) ranging between 5000 and 10(8) and between 10(−7) and 0.1, respectively. The proposed ANN demonstrates the relative error up to 0.07% which had the high accuracy compared with the vast majority of the precise explicit approximations of the Colebrook equation. Hindawi Publishing Corporation 2016 2016-04-03 /pmc/articles/PMC4834174/ /pubmed/27127498 http://dx.doi.org/10.1155/2016/5242596 Text en Copyright © 2016 D. Brkić and Ž. Ćojbašić. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Brkić, Dejan Ćojbašić, Žarko Intelligent Flow Friction Estimation |
title | Intelligent Flow Friction Estimation |
title_full | Intelligent Flow Friction Estimation |
title_fullStr | Intelligent Flow Friction Estimation |
title_full_unstemmed | Intelligent Flow Friction Estimation |
title_short | Intelligent Flow Friction Estimation |
title_sort | intelligent flow friction estimation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834174/ https://www.ncbi.nlm.nih.gov/pubmed/27127498 http://dx.doi.org/10.1155/2016/5242596 |
work_keys_str_mv | AT brkicdejan intelligentflowfrictionestimation AT cojbasiczarko intelligentflowfrictionestimation |