Numerical and Levenberg–Marquardt backpropagation neural networks computation of ternary nanofluid flow across parallel plates with Nield boundary conditions

The impact of the inclined magnetic field toward a flat parallel plate by operating incompressible suspension of three diverse types of oxide nano-sized particles in water-based ternary hybrid nano-liquid is investigated numerically. Flow is theoretically to be unstable squeezing the laminar flow of...

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Published in:	European physical journal plus Vol. 138; no. 1; p. 63
Main Authors:	Sharma, Ram Prakash, Madhukesh, J. K., Shukla, Sunendra, Prasannakumara, B. C.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 21.01.2023 Springer Nature B.V
Subjects:	Aluminum Applied and Technical Physics Atomic Back propagation networks Boundary conditions Complex Systems Compressing Computation Condensed Matter Physics Differential equations Energy Fluid flow Heat conductivity Heat exchangers Heat transfer Hyperthermia Inclination angle Investigations Laminar flow Magnetic effects Magnetic fields Mathematical and Computational Physics Mathematical models Molecular Nanofluids Nanoparticles Neural networks Optical and Plasma Physics Parallel plates Parameter sensitivity Partial differential equations Physics Physics and Astronomy Radiation Regular Article Similarity solutions Theoretical Velocity Velocity distribution Viscosity
ISSN:	2190-5444, 2190-5444
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Abstract	The impact of the inclined magnetic field toward a flat parallel plate by operating incompressible suspension of three diverse types of oxide nano-sized particles in water-based ternary hybrid nano-liquid is investigated numerically. Flow is theoretically to be unstable squeezing the laminar flow of ternary nanofluid between infinite parallel plates with Nield boundary conditions with the help of neural networks computation taken. The surface is subjected to a steady fully developed free stream velocity with Cattaneo–Christov heat and mass flux used to mathematical model with the governing equations in the form of partial differential equations of flow, and thermal profile, including the boundary conditions. The entailed similarity solution to the problem changed into a system of ordinary differential equations and resolved to utilize RKF 45 with shooting technique. The impact of these processes' sensitivity of the liquid parameterized by different non-dimensional parameters has been discussed on usual profiles along with Sherwood number and Nusselt number with the characteristics with the support of plots and tables. The study reveals that for squeezing parameter S 1 < 0 velocity profile decays and is enhanced for S 1 > 0 . Increasing the magnetic effect decreases the velocity profile, whereas increasing the inclination angle increases the velocity profile. The developed ANN model was proved to be trustworthy due to its excellent accuracy throughout the training, validation, and testing processes.
AbstractList	The impact of the inclined magnetic field toward a flat parallel plate by operating incompressible suspension of three diverse types of oxide nano-sized particles in water-based ternary hybrid nano-liquid is investigated numerically. Flow is theoretically to be unstable squeezing the laminar flow of ternary nanofluid between infinite parallel plates with Nield boundary conditions with the help of neural networks computation taken. The surface is subjected to a steady fully developed free stream velocity with Cattaneo–Christov heat and mass flux used to mathematical model with the governing equations in the form of partial differential equations of flow, and thermal profile, including the boundary conditions. The entailed similarity solution to the problem changed into a system of ordinary differential equations and resolved to utilize RKF 45 with shooting technique. The impact of these processes' sensitivity of the liquid parameterized by different non-dimensional parameters has been discussed on usual profiles along with Sherwood number and Nusselt number with the characteristics with the support of plots and tables. The study reveals that for squeezing parameter S 1 < 0 velocity profile decays and is enhanced for S 1 > 0 . Increasing the magnetic effect decreases the velocity profile, whereas increasing the inclination angle increases the velocity profile. The developed ANN model was proved to be trustworthy due to its excellent accuracy throughout the training, validation, and testing processes. The impact of the inclined magnetic field toward a flat parallel plate by operating incompressible suspension of three diverse types of oxide nano-sized particles in water-based ternary hybrid nano-liquid is investigated numerically. Flow is theoretically to be unstable squeezing the laminar flow of ternary nanofluid between infinite parallel plates with Nield boundary conditions with the help of neural networks computation taken. The surface is subjected to a steady fully developed free stream velocity with Cattaneo–Christov heat and mass flux used to mathematical model with the governing equations in the form of partial differential equations of flow, and thermal profile, including the boundary conditions. The entailed similarity solution to the problem changed into a system of ordinary differential equations and resolved to utilize RKF 45 with shooting technique. The impact of these processes' sensitivity of the liquid parameterized by different non-dimensional parameters has been discussed on usual profiles along with Sherwood number and Nusselt number with the characteristics with the support of plots and tables. The study reveals that for squeezing parameter S1<0 velocity profile decays and is enhanced for S1>0. Increasing the magnetic effect decreases the velocity profile, whereas increasing the inclination angle increases the velocity profile. The developed ANN model was proved to be trustworthy due to its excellent accuracy throughout the training, validation, and testing processes.
ArticleNumber	63
Author	Madhukesh, J. K. Shukla, Sunendra Prasannakumara, B. C. Sharma, Ram Prakash
Author_xml	– sequence: 1 givenname: Ram Prakash surname: Sharma fullname: Sharma, Ram Prakash organization: Department of Mechanical Engineering, National Institute of Technology Arunachal Pradesh – sequence: 2 givenname: J. K. surname: Madhukesh fullname: Madhukesh, J. K. organization: Department of studies in Mathematics, Davangere University – sequence: 3 givenname: Sunendra surname: Shukla fullname: Shukla, Sunendra organization: Department of Basic and Applied Science, National Institute of Technology – sequence: 4 givenname: B. C. orcidid: 0000-0003-1950-4666 surname: Prasannakumara fullname: Prasannakumara, B. C. email: dr.bcprasanna@gmail.com organization: Department of studies in Mathematics, Davangere University
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SubjectTerms	Aluminum Applied and Technical Physics Atomic Back propagation networks Boundary conditions Complex Systems Compressing Computation Condensed Matter Physics Differential equations Energy Fluid flow Heat conductivity Heat exchangers Heat transfer Hyperthermia Inclination angle Investigations Laminar flow Magnetic effects Magnetic fields Mathematical and Computational Physics Mathematical models Molecular Nanofluids Nanoparticles Neural networks Optical and Plasma Physics Parallel plates Parameter sensitivity Partial differential equations Physics Physics and Astronomy Radiation Regular Article Similarity solutions Theoretical Velocity Velocity distribution Viscosity
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Title	Numerical and Levenberg–Marquardt backpropagation neural networks computation of ternary nanofluid flow across parallel plates with Nield boundary conditions
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