A novel comparative analysis between the experimental and numeric methods on viscosity of zirconium oxide nano fluid: Developing optimal artificial neural network and new mathematical model

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:24:36Z
dc.date.available2024-11-07T13:24:36Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, the viscosity of five different ZrO2/Water nanofluids of 0.0125%, 0.025%, 0.05%, 0.1% and 0.2% prepared by the two-step method were experimentally investigated. Using the experimental data obtained, a multi-layer perceptron feed-forward back-propagation artificial neural network and a new mathematical correlation have been developed in order to predict the viscosity of ZrO2/Water nanofluid. Experimental results revealed that viscosity decreases with increasing temperature and increases with increasing concentration. The outputs obtained from the developed artificial neural network and the new correlation were compared with the experimental results and analyzed. The results show that the developed artificial neural network can predict the viscosity of ZrO2/Water nanofluid with an average error rate of -0.11%. The new mathematical model developed has been able to calculate the viscosity of ZrO2/Water nanofluid with an error rate of -0.74%. (C) 2020 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.powtec.2020.12.053
dc.identifier.endpage351
dc.identifier.issn0032-5910
dc.identifier.issn1873-328X
dc.identifier.scopus2-s2.0-85099249987
dc.identifier.scopusqualityQ1
dc.identifier.startpage338
dc.identifier.urihttps://doi.org/10.1016/j.powtec.2020.12.053
dc.identifier.urihttps://hdl.handle.net/11480/14214
dc.identifier.volume381
dc.identifier.wosWOS:000614004200005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofPowder Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectZirconium oxide
dc.subjectNanofluid
dc.subjectViscosity
dc.subjectArtificial neural network
dc.subjectCorrelation
dc.titleA novel comparative analysis between the experimental and numeric methods on viscosity of zirconium oxide nano fluid: Developing optimal artificial neural network and new mathematical model
dc.typeArticle

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