Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
Abstract 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 bott...
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Nature Portfolio
2021
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oai:doaj.org-article:94f2fc48996f432285d328a8a436a80b2021-12-02T14:16:58ZPrediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm10.1038/s41598-021-81957-32045-2322https://doaj.org/article/94f2fc48996f432285d328a8a436a80b2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81957-3https://doaj.org/toc/2045-2322Abstract 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.Meisam BabanezhadSamyar ZabihiIman BehroyanAli Taghvaie NakhjiriAzam MarjaniSaeed ShirazianNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021) |
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Medicine R Science Q Meisam Babanezhad Samyar Zabihi Iman Behroyan Ali Taghvaie Nakhjiri Azam Marjani Saeed Shirazian Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm |
description |
Abstract 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. |
format |
article |
author |
Meisam Babanezhad Samyar Zabihi Iman Behroyan Ali Taghvaie Nakhjiri Azam Marjani Saeed Shirazian |
author_facet |
Meisam Babanezhad Samyar Zabihi Iman Behroyan Ali Taghvaie Nakhjiri Azam Marjani Saeed Shirazian |
author_sort |
Meisam Babanezhad |
title |
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_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_sort |
prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/94f2fc48996f432285d328a8a436a80b |
work_keys_str_mv |
AT meisambabanezhad predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm AT samyarzabihi predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm AT imanbehroyan predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm AT alitaghvaienakhjiri predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm AT azammarjani predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm AT saeedshirazian predictionofgasvelocityintwophaseflowusingdevelopedfuzzylogicsystemwithdifferentialevolutionalgorithm |
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1718391620101996544 |