This paper investigates the performance of four nano-refrigerants (CuO-R113a, Al2O3-R134a, ZnO-R152a, TiO2-R600a) in terms of coefficient of performance and compressor power consumption using a MATLAB-Simulink two-phase flow domain Vapor Compression Refrigeration cycle. The analyses are done for volume concentrations of 0.1%, 0.3%, and 0.5% of nanoparticles in the base refrigerants. The results are derived mathematically in the Simulink model. The thermophysical properties of base-refrigerants were derived using the NIST Chemistry webbook and various mathematical models were applied to base refrigerants to calculate the properties of nano-refrigerants. The interpolation of the Liquid-vapor region was done using MS Excel. It was found that nano-refrigerants have better heat transfer characteristics and showed the best performance at a lower optimum concentration of 0.1%. Nano-refrigerant combinations have been tested in real-time and model validations; inferences have been duly reported.
In this paper viability of the Nano-refrigerants as a replacement for conventional coolants in bringing down energy consumption and thereby contribute to the green economy has been reviewed. The influence of the % of nanoparticle concentration in thermal conductivity, heat transfer
characteristics, and system performance in a refrigeration system is analysed. In this paper, the use of MHD and NEPCM were also discussed and reviewed for their useful impact in the field of nano refrigeration. Review analysis indicated that the maximum coefficient of performance, i.e., 18.75%
of enhancement, was observed when the TiO2 nanoparticle was added to the R134a refrigerant. Whereas in the case of the power consumption, Al2O3/R134a gives a 27% reduction in power consumption compared to the conventional fluids. Energy-saving of Al2O3/R134a
nano-refrigerant is more than 5 times and 80% more efficient compared to R134a/CuO. Similarly, Al2O3/R134a is 50% more efficient than R134a/SiO2 and 3.4% more efficient than R134a/TiO2. However, R134a/TiO2 exhibited a 54.7% increment in
the value of COP compared to R134a/Al2O3. Also, R134a/TiO2 displayed 60% and 35.2% of increment in COP in contrast to R134a/CuO, R134a/SiO2 respectively. The analysis recommends R134a/TiO2 as the best nano-refrigerant as its COP is the
highest of all with the energy savings on par with the Al2O3/R134a.
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.