Numerical Investigation of Heat Transfer Enhancement of a Water/Ethylene Glycol Mixture with Al2O3-TiO2 Nanoparticles

Alshehri, Fahad, Goraniya, Jaydeep and Combrinck, Madeleine (2020) Numerical Investigation of Heat Transfer Enhancement of a Water/Ethylene Glycol Mixture with Al2O3-TiO2 Nanoparticles. Applied Mathematics and Computation, 369. p. 124836. ISSN 0096-3003

[img] Text
Paper_Elsevier.pdf - Accepted Version
Restricted to Repository staff only until 11 November 2020.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (796kB) | Request a copy
Official URL: https://doi.org/10.1016/j.amc.2019.124836

Abstract

This paper presents a numerical study of a four-component hybrid nanofluid consisting of binary nanoparticles, Al2O3 and TiO2, dispersed into a double base fluid mixture of water and ethylene glycol. The nanofluid were modelled as a single phase fluid with volume concentrations of 2.5% Al2O3-1.5% TiO2 and 5% Al2O3-3% TiO2 respectively. The nanoparticles are suspended in a double base fluid of water and ethylene glycol mixture with a 70:30 volume ratio. The simulations were conducted for turbulenct flow through a pipe at working temperatures of 293 K and varying Reynolds numbers (7800-2000). Constant heat flux of 129983 W/m2 heat flux was applied to the pipe wall. The thermal conductivity was enhanced by 24 % and 11% at concentrations of 5-3% and 2.5-1.5%, respectively. While, viscosity of hybrid nanofluids was rising up to 70% and 67% at the same concentration. The avarage heat transfer coefficient of Al2O3-TiO2 hybrid nanofluids were enhanced with increase of temperature and volume concentration. It was noted that the maximum heat transfer enhancement is 52% higher than the base fluid for a volume concentration of 5-3%. There is a slight increase in the friction factor of Al2O3-TiO2 hybrid nanofluids with higher volume concentration.

Item Type: Article
Uncontrolled Keywords: Hybrid nano fluid, single phase approximation, viscosity, thermal conductivity, performance factor
Subjects: G100 Mathematics
G400 Computer Science
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 04 Nov 2019 15:51
Last Modified: 11 Nov 2019 16:45
URI: http://nrl.northumbria.ac.uk/id/eprint/41352

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics