In this work, turbulent convective heat transfer of propylene (R1270)-based nanorefrigerant in a circular tube with a uniform heat flux of 20 kW/m 2 is numerically investigated using different types of nanoparticles namely Al 2 O 3 , CuO, SiO 2 and ZnO with a volume concentration ranging from 0 to 5%. Computations have been carried out using the commercial CFD code Fluent for Reynolds number ranging from 20,000 to 100,000 and a nanoparticle diameter of 30 nm. Results in terms of the average convective heat transfer coefficients of both pure R1270 and R1270-based nanorefrigerants have been compared successfully to values obtained using correlations from the literature. It is found that among nanorefrigerants studied, R1270/CuO performs the best, followed in order by R1270/Al 2 O 3 , R1270/ZnO and R1270/SiO 2. It is also shown that the convective heat transfer coefficient is enhanced by increasing the Reynolds number and the nanoparticles volume concentration.
The present paper aims to numerically investigate the flow, heat transfer and entropy generation of some hydrocarbon based nanorefrigerants flowing in a circular tube subject to constant heat flux boundary condition. Numerical tests have been performed for 4 types of nanoparticles, namely Al2O3, CuO, SiO2, and ZnO with a diameter equal to 30 nm and a volume concentration of φ = 5%. These nanoparticles are dispersed in some hydrocarbon-based refrigerants, namely tetrafluoroethane (R134a), propane (R290), butane (R600), isobutane (R600a) and propylene (R1270). Computations have been performed for Reynolds number ranging from 600 to 2200. The numerical results in terms of the average heat transfer coefficient of pure refrigerants have been compared to values obtained using correlations from the literature. The results show that the increase of the Reynolds number increases the heat transfer coefficient and decreases the total entropy generation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.