Investigation of flow parameters of Reiner-Philippoff nanofluid flow with higher-order slip properties, activation energy, and bioconvection by artificial neural networks

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:24:06Z
dc.date.available2024-11-07T13:24:06Z
dc.date.issued2022
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, the flow parameters of Reiner-Philippoff nanofluid flow with high-order slip properties, activation energy, and bioconvection have been analyzed using artificial neural networks (ANNs). Local Nusselt number (LNN), local Sherwood number (LSN), and motile density number (MDN) are considered as flow parameters. Numerical values have been obtained by numerical methods using flow equations. To estimate the flow parameters, three different ANN models have been designed. The Levenberg-Marquardt training algorithm is used in multilayer perceptron network models with 10 neurons in the hidden layers. In all, 70% of the data set has been used for training the models, 15% for validation, and 15% for testing. The performance analysis of the network models has been made by calculating the determined performance parameters. The R values for the LNN, LSN, and MDN parameters have been calculated as 0.99261, 0.98769, and 0.99102, respectively, and the average deviation values are -0.65%, 0.06%, and -0.11%, respectively. The attained outcomes showed that the ANNs can predict the LNN, LSN, and MDN, which are the flow parameters of the Reiner-Philippoff nanofluid flow, with high accuracy.
dc.identifier.doi10.1002/htj.22529
dc.identifier.endpage4949
dc.identifier.issn2688-4534
dc.identifier.issn2688-4542
dc.identifier.issue6
dc.identifier.scopus2-s2.0-85127387253
dc.identifier.scopusqualityQ2
dc.identifier.startpage4929
dc.identifier.urihttps://doi.org/10.1002/htj.22529
dc.identifier.urihttps://hdl.handle.net/11480/13916
dc.identifier.volume51
dc.identifier.wosWOS:000776966700001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofHeat Transfer
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectactivation energy
dc.subjectartificial neural network
dc.subjectbioconvection flow
dc.subjecthigher-order slip
dc.subjectReiner-Philippoff nanofluid
dc.titleInvestigation of flow parameters of Reiner-Philippoff nanofluid flow with higher-order slip properties, activation energy, and bioconvection by artificial neural networks
dc.typeArticle

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