Hybrid FEM-neural network approach to radiative slip flow of TiO–SiO nanofluid over stretching surfaces.
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| Title: | Hybrid FEM-neural network approach to radiative slip flow of TiO–SiO nanofluid over stretching surfaces. |
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| Authors: | Jyothi, K.1 (AUTHOR) jyothi.bs@gprec.ac.in, Lingaswamy, A. P.2 (AUTHOR) |
| Source: | Theoretical & Mathematical Physics. Jun2025, Vol. 223 Issue 3, p1000-1015. 16p. |
| Subjects: | Thermal boundary layer, Complex fluids, Nonlinear differential equations, Ordinary differential equations, Reactive flow |
| Abstract: | We study the thermal performance and chemical reactive flow of a hybrid nanofluid over a stretching sheet heat generation. Titanium oxide (TiO ) and silicon dioxide (SiO ) combine to form a hybrid nanofluid, which is an improper fluid with water, Eg as a general fluid. Using a suitable similarity variable, the constitutive partial differential equations are converted into a system of connected nonlinear ordinary differential equations. The resulting equations are then solved numerically using the efficient finite element analysis method with the help of Mathematica 10.4 software and, for better results, with the Neural Network Levenberg–Marquardt method in MATLAB R2017b. The present study can be useful in precision engineering and nanotechnology tasks such as developing microfluidic devices and biomedical apparatuses where nanofluid flow control is crucial. The model assists in understanding fluid dynamics for complex cooling systems, particularly in industries where efficient heat transfer is essential, such as electronics and aerospace. Surface tension plays a major role in determining the uniformity and quality of thin films, and therefore it can also be advantageous in coating technologies and material processing. Our results reveal that increasing the volume fraction parameters and results in a thicker thermal boundary layer in both steady and unsteady states. Higher values of and enhance the velocity profile while reducing the velocity profile for both steady and unsteady states of TiO /SiO –water/Eg hybrid nanofluid. The results show that thermal conductivity performance of the hybrid nanofluid model is efficient compared with a single nanofluid. [ABSTRACT FROM AUTHOR] |
| Copyright of Theoretical & Mathematical Physics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 186156947 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Hybrid FEM-neural network approach to radiative slip flow of TiO–SiO nanofluid over stretching surfaces. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jyothi%2C+K%2E%22">Jyothi, K.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jyothi.bs@gprec.ac.in</i><br /><searchLink fieldCode="AR" term="%22Lingaswamy%2C+A%2E+P%2E%22">Lingaswamy, A. P.</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Theoretical+%26+Mathematical+Physics%22">Theoretical & Mathematical Physics</searchLink>. Jun2025, Vol. 223 Issue 3, p1000-1015. 16p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Thermal+boundary+layer%22">Thermal boundary layer</searchLink><br /><searchLink fieldCode="DE" term="%22Complex+fluids%22">Complex fluids</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+differential+equations%22">Nonlinear differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Ordinary+differential+equations%22">Ordinary differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Reactive+flow%22">Reactive flow</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We study the thermal performance and chemical reactive flow of a hybrid nanofluid over a stretching sheet heat generation. Titanium oxide (TiO ) and silicon dioxide (SiO ) combine to form a hybrid nanofluid, which is an improper fluid with water, Eg as a general fluid. Using a suitable similarity variable, the constitutive partial differential equations are converted into a system of connected nonlinear ordinary differential equations. The resulting equations are then solved numerically using the efficient finite element analysis method with the help of Mathematica 10.4 software and, for better results, with the Neural Network Levenberg–Marquardt method in MATLAB R2017b. The present study can be useful in precision engineering and nanotechnology tasks such as developing microfluidic devices and biomedical apparatuses where nanofluid flow control is crucial. The model assists in understanding fluid dynamics for complex cooling systems, particularly in industries where efficient heat transfer is essential, such as electronics and aerospace. Surface tension plays a major role in determining the uniformity and quality of thin films, and therefore it can also be advantageous in coating technologies and material processing. Our results reveal that increasing the volume fraction parameters and results in a thicker thermal boundary layer in both steady and unsteady states. Higher values of and enhance the velocity profile while reducing the velocity profile for both steady and unsteady states of TiO /SiO –water/Eg hybrid nanofluid. The results show that thermal conductivity performance of the hybrid nanofluid model is efficient compared with a single nanofluid. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Theoretical & Mathematical Physics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1134/S0040577925060133 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 1000 Subjects: – SubjectFull: Thermal boundary layer Type: general – SubjectFull: Complex fluids Type: general – SubjectFull: Nonlinear differential equations Type: general – SubjectFull: Ordinary differential equations Type: general – SubjectFull: Reactive flow Type: general Titles: – TitleFull: Hybrid FEM-neural network approach to radiative slip flow of TiO–SiO nanofluid over stretching surfaces. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jyothi, K. – PersonEntity: Name: NameFull: Lingaswamy, A. P. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00405779 Numbering: – Type: volume Value: 223 – Type: issue Value: 3 Titles: – TitleFull: Theoretical & Mathematical Physics Type: main |
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