Levenberg–Marquardt back-propagation algorithm for a developing unsteady hybrid nanofluid mixed convective flow across a revolving sphere: irreversibility analysis

Enhanced thermal conductivity and shielding applications in electronic devices, solar collectors and concentrators have motivated researchers to deal with the study of nanofluid modelling in the presence of rotating sphere. In this study, a detailed investigation has been conducted on a rotating sph...

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Bibliographic Details
Published in:European physical journal plus Vol. 139; no. 11; p. 1050
Main Authors: Chakraborty, Anomitra, Janapatla, Pranitha, Chatterjee, Basudeb
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 30.11.2024
Springer Nature B.V
Subjects:
Algorithms
Applied and Technical Physics
Artificial neural networks
Atomic
Back propagation
Back propagation networks
Brownian motion
Coefficient of friction
Complex Systems
Condensed Matter Physics
Convective flow
Differential equations
Dimensionless analysis
Energy conversion
Entropy
Fluid flow
Heat conductivity
Heat exchangers
Heat transfer
Investigations
Magnetic properties
Mathematical and Computational Physics
Molecular
Nanofluids
Nanoparticles
Neural networks
Nonlinear differential equations
Nusselt number
Optical and Plasma Physics
Parameters
Physical properties
Physics
Physics and Astronomy
Propagation velocity
Radiation
Regular Article
Rotating spheres
Skin friction
Solar collectors
Solar radiation shielding
Spheres
Theoretical
Thermal analysis
Thermal conductivity
Thermodynamics
ISSN:2190-5444, 2190-5444
Online Access:Get full text
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Summary:Enhanced thermal conductivity and shielding applications in electronic devices, solar collectors and concentrators have motivated researchers to deal with the study of nanofluid modelling in the presence of rotating sphere. In this study, a detailed investigation has been conducted on a rotating sphere using the Tiwari–Das model in the presence of radiation, magnetic and buoyancy effects to carry out thermal analysis and irreversibility analysis using various external parameters. The energy conversion effects have been captured using irreversibility analysis based on second law of thermodynamics. The dimensionless nonlinear ordinary differential equations were solved numerically using MATLAB bvp4c code, and back-propagation analysis was performed with the aid of ANN (artificial neural network). The outcomes reveal a surge in velocity along the x-direction with the unsteadiness parameter ( A ) , showing that the mono-nanofluid surpasses the hybrid nanofluid in velocity. Conversely, the z-direction velocity displays a reverse trend. There is an enhancement in the entropy of the system with augmenting radiation ( R ) and magnetic parameter ( M ) . The skin friction coefficient decreased by 2.93–4.51% on increasing the unsteadiness parameter ( A ) . Nusselt number increased with increasing rotational parameter λ . Entropy of the system N G and Bejan number ( B e ) increased with increasing R values. The maximum absolute error was of the order of 10 - 11 . The maximum mean squared error for Nusselt number was 3.0251E-11, which was attained in 441 epochs.
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ISSN:2190-5444
2190-5444
DOI:10.1140/epjp/s13360-024-05867-9