Open Access

ARTICLE

MHD Convective Flow of CNT/Water-Nanofluid in a 3D Cavity Incorporating Hot Cross-Shaped Obstacle

Faiza Benabdallah¹, Kaouther Ghachem¹, Walid Hassen², Haythem Baya², Hind Albalawi³, Lioua Kolsi^4,*

1 Department of Industrial and Systems Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
2 Laboratory of Metrology and Energy Systems, University of Monastir, Monastir, 5000, Tunisia
3 Department of Physics, College of Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
4 Department of Mechanical Engineering, College of Engineering, University of Ha’il, Ha’il, 81451, Saudi Arabia

* Corresponding Author: Lioua Kolsi. Email:

(This article belongs to the Special Issue: Computational Methods in Mono/hybrid nanofluids: Innovative Applications and Future Trends)

Computer Modeling in Engineering & Sciences 2025, 145(2), 1839-1861. https://doi.org/10.32604/cmes.2025.071678

Received 10 August 2025; Accepted 28 October 2025; Issue published 26 November 2025

Abstract

Current developments in magnetohydrodynamic (MHD) convection and nanofluid engineering technology have have greatly enhanced heat transfer performance in process systems, particularly through the use of carbon nanotube (CNT)–based fluids that offer exceptional thermal conductivity. Despite extensive research on MHD natural convection in enclosures, the combined effects of complex obstacle geometries, magnetic fields, and CNT nanofluids in three-dimensional configurations remain insufficiently explored. This research investigates MHD natural convection of carbon nanotube (CNT)-water nanofluid within a three-dimensional cavity. The study considers an inclined cross-shaped hot obstacle, a configuration not extensively explored in previous works. The work aims to elucidate the combined effects of CNT nanofluid concentration, magnetic field strength, and obstacle inclination on fluid flow patterns and heat transfer characteristics. Numerical simulations are performed using the finite element method (FEM) based on the Galerkin Weighted Residual approach. The analysis systematically considers variations in Rayleigh number (Ra), Hartmann number (Ha), nanoparticle volume fraction (Φ), and obstacle inclination angle (θ). Results show that increasing Ra from 10³ to 10⁶ enhances convective heat transfer by up to 228%, while raising the CNT volume fraction to 4.5% improves heat transfer by about 64%. In contrast, strengthening the magnetic field from Ha = 0 to Ha = 100 suppresses fluid motion and reduces heat transfer by nearly 67%, whereas varying the obstacle inclination from 0° to 45° leads to a 4.6% decrease in efficiency. The addition of nanoparticles slightly increases viscosity, reducing flow intensity by 8.3% when Ha = 0. Furthermore, a novel multiparametric correlation is proposed, accurately predicting the average Nusselt number as a function of Ra, Ha, ϕ, and θ, with an R² of 0.98. These findings provide new insights into the role of geometry, magnetic effects, and nanofluids in heat transfer enhancement, offering practical guidance for the design and optimization of advanced thermal systems.

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