Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1660 - 1660

Published: March 26, 2025

Highlighting the importance of artificial intelligence and machine learning approaches in engineering fluid mechanics problems, especially heat transfer applications is main goal presented article. With advancement Artificial Intelligence (AI) Machine Learning (ML) techniques, computational efficiency accuracy numerical results are enhanced. The theme study to use techniques examine thermal analysis MHD boundary layer flow Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder embedded porous medium with source/sink viscous dissipation effects. considered base water (H2O) hybrid nanoparticles titanium oxide (TiO2) Copper (CuO). governing equations nonlinear PDEs. Non-similar system PDEs obtained efficient conversion variables. dimensionless truncated using local non-similarity approach up third level solution evaluated MATLAB built-in-function bvp4c. Neural Networks (ANNs) simulation used trained networks predict behavior. Thermal improves enhancement value Rd. reliability ANNs predicted addressed computation correlation index residual analysis. RMSE [0.04892, 0.0007597, 0.0007596, 0.01546, 0.008871, 0.01686] for various scenarios. It observed that when concentration increases then characteristics cylinder.

Language: Английский

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Computational Role of Polymer‐Based Ternary Hybrid Nanofluid Between Convergent/Divergent Channels With Radiation and Stretchable/Shrinkable Wall Effects

Journal of Mathematics, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

The present article introduces a numerical and analytical study of ternary hybrid nanoparticle (Cu, Fe 3 O 4 , SiO 2 ) with base fluid Polymer. Heat Transfer on MHD Jeffery–Hamel flow multiple effects is taken into account. Innovative results in the current are obtained by utilizing combined effect nonlinear thermal radiation stretchable/shrinkable walls. modelled partial differential equations underwent transformation to ordinary using similarity transformation. Subsequently, an solution was employing ADM method. To validate accuracy results, comparison made outcomes from HAM‐based Mathematica package Runge–Kutta–Fehlberg fourth‐fifth order approach featuring shooting technique. diverse parameters dimensionless velocity, temperature profiles, skin friction coefficient Nusselt number has been investigated interpreted through tabular graphical results. When nanoparticles fluid, rate heat transmission upsurged for both convergent‐divergent channels. In addition, boosts augment volume fraction. Results also reveal that nanofluid upsurges stretching zone ( C > 0) drops shrinking < 0).

Language: Английский

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Thermal and flow characteristics of tetra-hybrid nanofluid over a stretching/shrinking inclined cylinder: Influence of heat absorption and quadratic radiation

Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(2), P. 101513 - 101513

Published: April 16, 2025

Language: Английский

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A cross-fluid heat transfer analysis using neural networks over porous rotating disk

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(9)

Published: Sept. 1, 2024

This research explores the complex interaction of incompressible cross-fluid flow, heat, and mass transfer characteristics on a porous rotating disk. The study employs sophisticated mathematical methods, including similarity transformations, to convert governing partial differential equations into nonlinear ordinary equations. These are then solved using numerical method, fourth-class boundary value problem. We employ an Artificial Neural Networks algorithm with backpropagation Levenberg–Marquardt Scheme analyze heat mechanism quantitatively. Our results provide accurate values for Nusselt number, Sherwood skin friction coefficient. examination addresses this system's fluid mechanics transport phenomena potential applications in engineering industrial processes.

Language: Английский

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Intelligent computing applications to study the tri-hybrid nanofluid past over the stretched surface

Results in Physics, Journal Year: 2024, Volume and Issue: unknown, P. 107972 - 107972

Published: Sept. 1, 2024

Language: Английский

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