Thermal analysis for hybrid nanofluid past a cylinder exposed to magnetic field
Source abstract
Abstract
This work has developed mathematical models for thermal transport by treating Al2O3 as nanoparticles of a single type and Al2O3 and Cu as hybrid nanoparticles in a hyperbolic tangent fluid. The solution for the developed mathematical models is computed by FEM in order to compare the thermal performances of the nanofluid and hybrid nanofluid. The convergence, error, and mesh-free analyses are carried out to get physically realistic solutions so that useful information about the underlying thermal physics is extracted. Numerical experiments revealed that the momentum of stretching of the cylinder diffuses faster in a nanofluid than in a hybrid nanofluid. The heat generation rate in the hybrid nanofluid is higher than that in a nanofluid. Simulated results have also revealed that the thermal performance of the hybrid nanofluid is better than that of the nanofluid. Therefore, dispersing hybrid nanoparticles (combination of Cu and Al2O3) in a hyperbolic tangent fluid is recommended for efficient working fluids. Surprisingly, the wall shear stress for the hybrid nanofluid is higher than that of the nanofluid. Numerical data extracted from numerical experiments revealed that the wall heat transfer rate for a hybrid nanofluid is higher than that of the nanofluid. It is also observed that the rate of generation of heat in the hybrid nanofluid is greater than the rate of generation of heat in a nanofluid, which is a drawback of the hybrid nanofluid when it is treated as a coolant. The diffusion of the wall momentum in hybrid nanofluids is less than that in nanofluids. The hybrid nanofluid is a more efficient working fluid because of its high thermal performance when compared with the nanofluid. The intensity of the magnetic field causes a significant reduction in the flow and has a remarkable impact on the momentum boundary layer thickness.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Nanofluid Flow and Heat Transfer · Heat Transfer Mechanisms · Heat Transfer and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Mathematics Department, College of Science Al-Zulfi, Majmaah University 1 , Majmaah 11952, Saudi Arabia
Department of Applied Mathematics and Statistics, Institute of Space Technology 2 , Islamabad 44000, Pakistan
Funding
Higher Education Commission, Pakistan
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