Optimization of micro-rotation effect on magnetohydrodynamic nanofluid flow with artificial neural network

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dc.contributor.authorShafiq, Anum
dc.contributor.authorÇolak, Andaç Batur
dc.contributor.authorSindhu, Tabassum Naz
dc.date.accessioned2024-06-24T07:39:12Z
dc.date.available2024-06-24T07:39:12Z
dc.date.issued2024en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractIt is a major research area in mathematics, physics, engineering, and computer science to study the heat and mass transfer properties of flow. Suspensions containing multiple nanoparticles or nanocomposites have recently gained a wide range of applications in biological research and clinical trials under certain conditions. Nanofluids are important suspensions that allow nanoparticles to disseminate and behave in a homogeneous and stable environment. Therefore, here magnetohydrodynamic micropolar nanofluid flow towards the stretching surface with artificial neural network has been considered. In this study, radiation and heat source phenomena have been presented in heat convection. Brownian and thermophoresis effects and micro-rotational particles are also taking into account. The non-linear simplified equations have been calculated numerically via Runge-Kutta fourth-order shooting process. The calculation of the Sherwood number, Nusselt number, couple stress coefficient, and skin friction coefficient has been conducted utilizing diverse parameters. Furthermore, the outcomes have been employed to create four distinct artificial neural networks. Our observation indicates that an increase in the heat source quantity (Formula presented.) leads to a rise in heat generation, resulting in a greater total heat output and an increase in the temperature field. Coefficient of determination “R” values higher than 0.99 have been obtained for the artificial neural network models. The obtained findings have shown that artificial neural networks can predict thermal parameters with high accuracy.en_US
dc.identifier.doi10.1002/zamm.202300498en_US
dc.identifier.scopus2-s2.0-85196005247en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/7307
dc.identifier.urihttps://doi.org/10.1002/zamm.202300498
dc.identifier.wosWOS:001247876600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Incen_US
dc.relation.ispartofZAMM Zeitschrift fur Angewandte Mathematik und Mechaniken_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.titleOptimization of micro-rotation effect on magnetohydrodynamic nanofluid flow with artificial neural networken_US
dc.typeArticleen_US

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