Q1 2026

High-fidelity FEM–PARDISO simulation of entropy generation in MHD nanofluid flow through fractal-structured porous enclosures: Toward advanced thermal management in energy and biomedical systems

Kamran Khan · Saeed Islam · Muhammad Salim Khan · Amna · Zahir Shah
10.25259/jksus_1015_2025 390 المشاهدات 0 الاقتباسات
0
الاقتباسات
390
المشاهدات
الملخص


This study presents a high-fidelity numerical analysis of magnetohydrodynamic (MHD) convective heat transfer and entropy generation in a copper-based nanofluid within a porous enclosure embedded with multiscale fractal barriers. The Darcy–Forchheimer model captures nonlinear drag in the porous matrix, while the applied magnetic field influences buoyancy-driven flow. Simulations are performed using the finite element method (FEM) in COMSOL Multiphysics with the PARDISO solver. The objective is to evaluate how fractal barrier geometry, Rayleigh number (Ra), Hartmann number (Ha), Darcy number (Da), and porosity influence heat transfer and thermodynamic behavior. Results reveal that fractal barriers enhance convective mixing, break flow symmetry, and increase Nusselt number while reducing thermal stratification. Higher Ra significantly improves heat transfer (Nu
avg
up to 16.4%) but increases entropy generation, indicating a trade-off in thermal efficiency. Increasing Ha suppresses convection and reduces Nu
avg
, S
Total
, and Be
avg
by up to 0.166%, 0.154%, and 0.095%, respectively. A higher Darcy number improves convective strength, while increased porosity raises Nu
avg
by 2.31% and S
Total
by 2.79%, but lowers Be
avg
by 0.98%. These insights support the application of fractal-structured porous systems for advanced thermal management in energy, electronics, and biomedical engineering.

الاستشهاد بهذا المقال (APA)
Kamran, K., Saeed, I., Muhammad, S. K., Amna, Zahir, S. (2026). High-fidelity FEM–PARDISO simulation of entropy generation in MHD nanofluid flow through fractal-structured porous enclosures: Toward advanced thermal management in energy and biomedical systems. Journal of King Saud University – Science. https://doi.org/10.25259/jksus_1015_2025
أبحاث ذات صلة
Short-term wind power prediction based on IBOA-AdaBoost-RVM
Yongliang Yuan; Qingkang Yang; Jianji Ren; Kunpeng Li; Zhenxi Wang; Yanan Li; Wu · 2024
33
استشهاد
402
A parametrized approach to generalized fractional integral inequalities: Hermite–Hadamard and Maclau…
Abdelghani Lakhdari; Bandar Bin-Mohsin; Fahd Jarad; Hongyan Xu; Badreddine Mefta · 2024
20
استشهاد
397
Modulatory effects of glutamic acid on growth, photosynthetic pigments, and stress responses in oliv…
Muhammad Hamzah Saleem; Sadia Zafar; Sadia Javed; Muhammad Anas; Temoor Ahmed; S · 2024
19
استشهاد
401
Cloud spot instance price forecasting multi-headed models tuned using modified PSO
Mohamed Salb; Luka Jovanovic; Ali Elsadai; Nebojsa Bacanin; Vladimir Simic; Drag · 2024
17
استشهاد
401
16
استشهاد
404
الوصول
عرض النص الكامل عبر DOI
نُشر في
الرقم الدولي ISSN 1018-3647
الربعية Q1
درجة المؤشر القياس العربي 100
التخصص Natural Sciences
الناشر King Saud University
الدولة 🇸🇦 Saudi Arabia
عرض ملف المجلة →
المؤلفون
تفاصيل النشر
السنة 2026
اللغة English
أُضيف في 14 Jul 2026