Optimization of the numerical treatment of the Darcy-Forchheimer flow of Ree-Eyring fluid with chemical reaction by using artificial neural networks

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.authoridSindhu, Tabassum/0000-0001-9433-4981
dc.contributor.authorShafiq, Anum
dc.contributor.authorColak, Andac Batur
dc.contributor.authorSindhu, Tabassum Naz
dc.date.accessioned2024-11-07T13:32:33Z
dc.date.available2024-11-07T13:32:33Z
dc.date.issued2023
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, Darcy Forchheimer flow paradigm, which is a useful paradigm in fields such as petroleum engineering where high flow velocity effects are common, has been analyzed with artificial intelligence approach. In this context, first of all, Darcy-Forchheimer flow of Ree-Eyring fluid along a permeable stretching surface with convective boundary conditions has been examined and heat and mass transfer mechanisms have been investigated by including the effect of chemical process, heat generation/absorption, and activation energy. Cattaneo-Christov heat flux model has been used to analyze heat transfer properties. Within the scope of optimizing Darcy-Forchheimer flow of Ree-Eyring fluid; three different artificial neural network models have been developed to predict Nusselt number, Sherwood number, and skin friction coefficient values. The developed artificial neural network model has been able to predict Nusselt number, Sherwood number, and skin friction coefficient values with high accuracy. The findings obtained as a result of the study showed that artificial neural networks are an ideal tool that can be used to model Darcy-Forchheimer Ree-Eyring fluid flow towards a permeable stretch layer with activation energy and a convective boundary condition.
dc.identifier.doi10.1002/fld.5147
dc.identifier.endpage192
dc.identifier.issn0271-2091
dc.identifier.issn1097-0363
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85138161844
dc.identifier.scopusqualityQ1
dc.identifier.startpage176
dc.identifier.urihttps://doi.org/10.1002/fld.5147
dc.identifier.urihttps://hdl.handle.net/11480/15464
dc.identifier.volume95
dc.identifier.wosWOS:000854365600001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofInternational Journal For Numerical Methods in Fluids
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 (ANN)
dc.subjectconvective boundary condition
dc.subjectheat generation
dc.subjectRee-Eyring fluid
dc.titleOptimization of the numerical treatment of the Darcy-Forchheimer flow of Ree-Eyring fluid with chemical reaction by using artificial neural networks
dc.typeArticle

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