Heat Transfer Study of a Ternary Hybrid Nanofluid Flow in a Rotating Horizontal Annulus Using Artificial Intelligence Computing Techniques: Application of Particle Swarm Optimization and Artificial Neural Network

This study investigates the influence of an axial magnetic field on the flow and Heat Transfer (HT) of a Ternary Hybrid Nanofluid in a rotating horizontal annulus between two coaxial tubes, considering the impact of viscous dissipation and thermal radiation. The study examines the use of spherical aluminum oxide (Al 2 O[Formula: see text] nanoparticles, platelet-shaped graphene and Cylindrical Carbon Nanotubes (CNTs). The velocity and temperature fields were transformed to get a system of Ordinary Differential Equations (ODEs) representing the flow and HT governing equations. A dataset is produced by systematically varying key parameters using the bvp4c function in MATLAB. Following this, two advanced artificial intelligence techniques, Artificial Neural Networks (ANNs) and Fuzzy Particle Swarm Optimization (FPSO), are utilized to forecast the Nusselt number. The effects of various parameters, including the radiation parameter, Reynolds number and Hartmann number on HT and flow characteristics were analyzed. Analysis of data presents that the Nusselt number increases with higher radiation parameter and falls with higher Hartmann number (Ha), Reynolds number and Eckert number. Furthermore, Nusselt number achieves higher values for Quadratic Thermal Radiation (QTR) case in comparison to Linear Thermal Radiation (LTR). It is observed that when value of radiation parameter is increased from 5.5 to 11.5, the Nusselt number values rises by 216.19% (when [Formula: see text]), 231.34% (when [Formula: see text]) and 249.82% (when [Formula: see text]) for LTR, whereas the Nusselt number values rises by 153.68% (when [Formula: see text]), 157.01% (when [Formula: see text]) and 160.70% (when [Formula: see text]) for QTR. The applications of the nanofluid flow inside a rotating horizontal annulus are seen in heat exchangers, gas turbines, rotating machinery, cylindrical solar collectors, medical devices like centrifuge and rotating drum dryers in food processing.

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Publication Details

Journal
NANO
Published
2025-01-10
DOI
https://doi.org/10.1142/s1793292025500316
Citations
7
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
4.72
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article

Heat Transfer Study of a Ternary Hybrid Nanofluid Flow in a Rotating Horizontal Annulus Using Artificial Intelligence Computing Techniques: Application of Particle Swarm Optimization and Artificial Neural Network

Moh Yaseen, Sanjalee Maheshwari, Sawan Kumar Rawat, Manish Pant
7 citations
NANO
Nanofluid Flow and Heat Transfer
4.72
article

Heat Transfer Study of a Ternary Hybrid Nanofluid Flow in a Rotating Horizontal Annulus Using Artificial Intelligence Computing Techniques: Application of Particle Swarm Optimization and Artificial Neural Network

Moh Yaseen, Sanjalee Maheshwari, Sawan Kumar Rawat, Manish Pant
article en
7 citations

Abstract

This study investigates the influence of an axial magnetic field on the flow and Heat Transfer (HT) of a Ternary Hybrid Nanofluid in a rotating horizontal annulus between two coaxial tubes, considering the impact of viscous dissipation and thermal radiation. The study examines the use of spherical aluminum oxide (Al 2 O[Formula: see text] nanoparticles, platelet-shaped graphene and Cylindrical Carbon Nanotubes (CNTs). The velocity and temperature fields were transformed to get a system of Ordinary Differential Equations (ODEs) representing the flow and HT governing equations. A dataset is produced by systematically varying key parameters using the bvp4c function in MATLAB. Following this, two advanced artificial intelligence techniques, Artificial Neural Networks (ANNs) and Fuzzy Particle Swarm Optimization (FPSO), are utilized to forecast the Nusselt number. The effects of various parameters, including the radiation parameter, Reynolds number and Hartmann number on HT and flow characteristics were analyzed. Analysis of data presents that the Nusselt number increases with higher radiation parameter and falls with higher Hartmann number (Ha), Reynolds number and Eckert number. Furthermore, Nusselt number achieves higher values for Quadratic Thermal Radiation (QTR) case in comparison to Linear Thermal Radiation (LTR). It is observed that when value of radiation parameter is increased from 5.5 to 11.5, the Nusselt number values rises by 216.19% (when [Formula: see text]), 231.34% (when [Formula: see text]) and 249.82% (when [Formula: see text]) for LTR, whereas the Nusselt number values rises by 153.68% (when [Formula: see text]), 157.01% (when [Formula: see text]) and 160.70% (when [Formula: see text]) for QTR. The applications of the nanofluid flow inside a rotating horizontal annulus are seen in heat exchangers, gas turbines, rotating machinery, cylindrical solar collectors, medical devices like centrifuge and rotating drum dryers in food processing.

NANOVol. 20(09)
Chandigarh University (IN), Central University of Himachal Pradesh (IN), Sardar Vallabhbhai Patel University of Agriculture & Technology (IN), Uttarakhand Government (IN), Indian Institute of Information Technology Una (IN), Graphic Era University (IN)
Clean water and sanitation
Openalex Percentile: Top 6%
Nanofluid Flow and Heat Transfer
4.72
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