This study investigates the utilization of a trapezoidal cavity with a corrugated bottom wall containing a Carreau hybrid nanofluid composed of water, aluminum, and copper nanoparticles. A heated, rotating cylinder is placed at the center of the enclosure in the presence of an external magnetic field. The impact of Forchheimer and Brinkman porous medium models on the hybrid nanofluid is examined. Three different inlet–outlet placement configurations are considered to investigate their influence on heat transfer. The governing equations for fluid flow and heat transfer are solved numerically. Through simulations, a range of flow-controlling variables is systematically adjusted, including the Darcy number, Reynolds number, Hartmann number, nanoparticle volume fraction, undulation on the hot bottom wall, power law index, and rotational speed of the inner heated cylinder. The results demonstrate that the hybrid nanofluid and rotating cylinder significantly enhance heat transfer within the trapezoidal cavity. Higher values of the Darcy number, Reynolds number, and nanoparticle volume fraction lead to increased heat transfer rates. The placement configuration of the inlet and outlet ports also affects heat transfer performance, with the bottom-top configuration yielding the best results. Furthermore, a comparative analysis of flow profiles and heat distribution is conducted using the multiple expression programing technique. The proposed model accurately predicts the flow and heat transfer characteristics in the trapezoidal cavity, as validated through comparison with provided data sets.
Skip Nav Destination
Article navigation
March 2024
Research Article|
March 08 2024
Intelligent prediction of non-Newtonian hybrid nanoparticle-enhanced fluid flow and heat transfer behaviours in a trapezoidal enclosure: Integrated simulation approach
Aneela Bibi
;
Aneela Bibi
(Conceptualization, Investigation, Methodology, Validation, Visualization, Writing – original draft)
1
State Key Lab of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University
, Shanghai 200240, China
Search for other works by this author on:
Hang Xu (徐航)
;
Hang Xu (徐航)
a)
(Conceptualization, Supervision, Validation, Writing – review & editing)
1
State Key Lab of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University
, Shanghai 200240, China
a)Author to whom correspondence should be addressed: [email protected]
Search for other works by this author on:
Naeem Ullah
Naeem Ullah
(Formal analysis, Methodology)
2
School of Mathematical Sciences, Jiangsu University
, Zhenjiang, Jiangsu 212013, China
Search for other works by this author on:
a)Author to whom correspondence should be addressed: [email protected]
Physics of Fluids 36, 033610 (2024)
Article history
Received:
January 13 2024
Accepted:
February 15 2024
Citation
Aneela Bibi, Hang Xu, Naeem Ullah; Intelligent prediction of non-Newtonian hybrid nanoparticle-enhanced fluid flow and heat transfer behaviours in a trapezoidal enclosure: Integrated simulation approach. Physics of Fluids 1 March 2024; 36 (3): 033610. https://doi.org/10.1063/5.0197679
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
Referee acknowledgment for 2024
Alan Jeffrey Giacomin
Chinese Academy of Science Journal Ranking System (2015–2023)
Cruz Y. Li (李雨桐), 李雨桐, et al.
Fall and breakup of miscible magnetic fluid drops in a Hele–Shaw cell
M. S. Krakov (М. С. Краков), М. С. Краков, et al.
Related Content
Numerical simulation and intelligent prediction of thermal transport of a water-based copper oxide nanofluid in a lid-driven trapezoidal cavity
Physics of Fluids (September 2023)
The effect of wider base location on the natural convection in a 3D partially heated trapezoidal cavity
AIP Conf. Proc. (July 2023)
Thermo-fluidic transport process in a novel M-shaped cavity packed with non-Darcian porous medium and hybrid nanofluid: Application of artificial neural network (ANN)
Physics of Fluids (March 2022)
Heat transfer by natural convection in an annular space partially porous layered and saturated by a nanofluid
AIP Conf. Proc. (October 2023)