Modeling of Darcy-Forchheimer bioconvective Powell Eyring nanofluid with artificial neural network

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.authoridSindhu, Tabassum/0000-0001-9433-4981
dc.authoridShafiq, Anum/0000-0001-7186-7216
dc.contributor.authorColak, Andac Batur
dc.contributor.authorShafiq, Anum
dc.contributor.authorSindhu, Tabassum Naz
dc.date.accessioned2024-11-07T13:32:40Z
dc.date.available2024-11-07T13:32:40Z
dc.date.issued2022
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractNano-engineering has recently grown to include the usages of nanoparticles in combination with base fluids to improve the thermal properties of pure fluids. Today's industry focuses primarily on thermal machine efficiency, and nanomaterials are the key to achieving this goal. The slip and Darcy-Forchheimer phenomena are studied for bioconvective implementations in a Powell-Eyring nanofluid model confined by a stretching surface via artificial neural network in current study. During the research, the activation energy, convective boundary condition and thermal radiation phenomena are considered as novel impacts. The governing expressions are formulated according to fundamental rules. Numerical simulations using a Runge-Kutta fourth order technique via shooting procedure are used to obtain the solution and then applies artificial neural network. A data set has been created for various flow scenarios, and developed an artificial neural network model to predict skin friction coefficient, local Sherwood number, local motile density of microorganisms and local Nusselt number values . The results of the study showed that the developed artificial neural network models can make predictions with very low error, not exceeding 0.53% on average.
dc.identifier.doi10.1016/j.cjph.2022.04.004
dc.identifier.endpage2453
dc.identifier.issn0577-9073
dc.identifier.scopus2-s2.0-85129501420
dc.identifier.scopusqualityQ2
dc.identifier.startpage2435
dc.identifier.urihttps://doi.org/10.1016/j.cjph.2022.04.004
dc.identifier.urihttps://hdl.handle.net/11480/15553
dc.identifier.volume77
dc.identifier.wosWOS:000805618600006
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofChinese Journal of Physics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectPowell-Eyring nanofluid
dc.subjectActivation energy
dc.subjectThermal radiation
dc.subjectArtificial neural network
dc.subjectDarcy-Forchheimer
dc.subjectBuongiorno?s nanofluid model
dc.titleModeling of Darcy-Forchheimer bioconvective Powell Eyring nanofluid with artificial neural network
dc.typeArticle

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