Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm

In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of rea...

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Autores principales: Babanezhad, Meisam, Zabihi, Samyar, Behroyan, Iman, Nakhjiri, Ali Taghvaie, Marjani, Azam, Shirazian, Saeed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840922/
https://www.ncbi.nlm.nih.gov/pubmed/33504889
http://dx.doi.org/10.1038/s41598-021-81957-3
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author Babanezhad, Meisam
Zabihi, Samyar
Behroyan, Iman
Nakhjiri, Ali Taghvaie
Marjani, Azam
Shirazian, Saeed
author_facet Babanezhad, Meisam
Zabihi, Samyar
Behroyan, Iman
Nakhjiri, Ali Taghvaie
Marjani, Azam
Shirazian, Saeed
author_sort Babanezhad, Meisam
collection PubMed
description In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of reactor, and the injected gas velocities were between 0.05 to 0.11 m/s. After doing a couple of training by making some changes in DE parameters and FIS parameters, the greatest percentage of FIS capacity was achieved. By applying the optimized model, the gas phase velocity in x direction inside the reactor was predicted when the injected gas velocity was 0.08 m/s.
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spelling pubmed-78409222021-01-28 Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm Babanezhad, Meisam Zabihi, Samyar Behroyan, Iman Nakhjiri, Ali Taghvaie Marjani, Azam Shirazian, Saeed Sci Rep Article In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of reactor, and the injected gas velocities were between 0.05 to 0.11 m/s. After doing a couple of training by making some changes in DE parameters and FIS parameters, the greatest percentage of FIS capacity was achieved. By applying the optimized model, the gas phase velocity in x direction inside the reactor was predicted when the injected gas velocity was 0.08 m/s. Nature Publishing Group UK 2021-01-27 /pmc/articles/PMC7840922/ /pubmed/33504889 http://dx.doi.org/10.1038/s41598-021-81957-3 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Babanezhad, Meisam
Zabihi, Samyar
Behroyan, Iman
Nakhjiri, Ali Taghvaie
Marjani, Azam
Shirazian, Saeed
Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title_full Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title_fullStr Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title_full_unstemmed Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title_short Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
title_sort prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840922/
https://www.ncbi.nlm.nih.gov/pubmed/33504889
http://dx.doi.org/10.1038/s41598-021-81957-3
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