Optimizing heat and mass transfer in Carreau nanofluid with mixed nanoparticles in porous media using explicit finite difference method

Ali Haider, M. S. Anwar, Yufeng Nie, Fahad Saleh Almubaddel, Magda Abd El-Rahman

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Purpose: This study investigates the effects of hybrid nanoparticles on thermal performance, focusing on convection, magnetic fields, diffusion, radiation, and chemical reactions in porous media. An H2O-based fractional Carreau hybrid nanofluid is utilized to enhance heat transfer for industrial applications like gas turbines and condensers. Design/Methodology/Approach: The Caputo definition of fractional derivatives models the fluid flow, integrating integer and non-integer dynamics. The governing equations are dimensionally reduced and solved using the explicit finite difference method (EFD), with stability and convergence criteria ensuring accuracy. Key parameters, including the Sherwood and Nusselt numbers, are examined to understand thermal and mass transfer behavior. Findings: Results show that fractional exponents and thermophysical properties significantly influence flow behavior. Fluid velocity increases with the fractional exponent (α) due to reduced resistance, while higher porosity parameter (λ4) decreases velocity. The temperature gradient decreases by 20.31% with the fractional exponent (β) and by 22.87% with the Weissenberg number. Skin friction increases by 28.17% with the magnetic parameter, and higher thermal conductivity enhances temperature profiles.

Original languageEnglish
Article number105428
JournalCase Studies in Thermal Engineering
Volume64
DOIs
StatePublished - Dec 2024

Keywords

  • Explicit finite difference method
  • Fractional Carreau fluid
  • Hybrid nanoparticles
  • Porous media
  • Thermal radiations

Fingerprint

Dive into the research topics of 'Optimizing heat and mass transfer in Carreau nanofluid with mixed nanoparticles in porous media using explicit finite difference method'. Together they form a unique fingerprint.

Cite this