Computational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networking

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dc.authorid0000-0001-7492-4933en_US
dc.authorid0000-0001-9297-8134en_US
dc.contributor.authorRehman, Khalil Ur
dc.contributor.authorShatanawi, Wasfi
dc.contributor.authorÇolak, Andaç Batur
dc.date.accessioned2023-10-30T12:21:54Z
dc.date.available2023-10-30T12:21:54Z
dc.date.issued2023en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractIn this article, we constructed an artificial neural networking model for the stagnation point flow of Casson fluid towards an inclined stretching cylindrical surface. The Levenberg–Marquardt training technique is used in multilayer perceptron network models. Tan–Sig and purelin transfer functions are carried in the layers. For better novelty, heat and mass transfer aspects are taken into account. The viscous dissipation, thermal radiations, variable thermal conductivity, and heat generation effects are considered by way of an energy equation while the chemical reaction effect is calculated by use of the concentration equation. The flow is mathematically modelled for magnetic and non-magnetic flow fields. The flow equations are solved by the shooting method and the outcomes are concluded by means of line graphs and tables. The skin friction coefficient is evaluated at the cylindrical surface for two different flow regimes and the corresponding artificial neural networking estimations are presented. The coefficient of determination values’ proximity to one and the low mean squared error values demonstrate that each artificial neural networking model predicts the skin friction coefficient with high accuracyen_US
dc.identifier.doi10.3390/math11020326en_US
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85146786032en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/6846
dc.identifier.urihttps://doi.org/10.3390/math11020326
dc.identifier.volume11en_US
dc.identifier.wosWOS:000927708400001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofMathematicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCasson fluid; mixed convection; thermal radiations; shooting method; artificial neural networking; Levenberg–Marquardt techniqueen_US
dc.titleComputational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networkingen_US
dc.typeArticleen_US

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