An experimental and artificial neural network investigation on the laminar flow of magnetorheological fluids through circular pipes

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dc.contributor.authorGedik, Engin
dc.contributor.authorKurt, Huseyin
dc.contributor.authorPala, Murat
dc.contributor.authorAlakour, Abdulla
dc.date.accessioned2024-02-23T14:12:52Z
dc.date.available2024-02-23T14:12:52Z
dc.date.issued2022
dc.departmentNEÜen_US
dc.description.abstractFluids can change their physical properties when they are exposed to magnetic fields. Magnetorheological (MR) fluids are classified as smart materials because their viscoelastic properties can increase by the application of the magnetic field. Accordingly, they are used in different engineering applications such as flow control and vibration damping. In this study, three different types of MR fluids flow in circular pipes with diameters of 10 and 15 mm and length of 300 mm were experimentally investigated with and without applying the magnetic field. An electromagnetic device was designed and manufactured in order to create a magnetic field induction for experiments. Throughout the experiments, the range of magnetic field induction value was B = 0-0.15 T, increased to 0.01 T. Based on the results obtained by the experimental study, it can be asserted that applying the magnetic field prompted an increase in the viscosity of MR fluids, leading to decreasing flow velocity. At B = 0.15 T, which is the highest value of the magnetic field, the flow velocity values dropped by 95%. Subsequently, the artificial neural networks algorithms are used in accordance with the obtained results to develop a correlation that clarifies the effect of the magnetic field on the flow velocity. The results show that the experimental and ANN models perform very similarly, and the ANN algorithm yields better results as a tool to predict the MR fluid flow behavior.en_US
dc.description.sponsorshipScientific and Technological Research Council of TURKEY (TUBITAK) [110M030]en_US
dc.description.sponsorshipAcknowledgement The authors would like to thank to the Scientific and Technological Research Council of TURKEY (TUBITAK) for providing the financial supports for this study under the 110M030 project.en_US
dc.identifier.doi10.1016/j.jmmm.2021.168893
dc.identifier.issn0304-8853
dc.identifier.issn1873-4766
dc.identifier.scopus2-s2.0-85120969735en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1016/j.jmmm.2021.168893
dc.identifier.urihttps://hdl.handle.net/20.500.12452/12220
dc.identifier.volume546en_US
dc.identifier.wosWOS:000778428900007en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal Of Magnetism And Magnetic Materialsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMagnetorheological Fluiden_US
dc.subjectMagnetic Fielden_US
dc.subjectLaminar Flowen_US
dc.subjectArtificial Neural Networken_US
dc.titleAn experimental and artificial neural network investigation on the laminar flow of magnetorheological fluids through circular pipesen_US
dc.typeArticleen_US

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