Water-based Al2O3, CuO and TiO2 nanofluids as secondary fluids for refrigeration systems: a thermal conductivity study

Abstract

The existing models for predicting the thermal conductivity of nanofluid are not suitable for R718 (water)-based applications due to its lower working temperature as compared to other heat transfer fluids. R718 is used as a secondary refrigerant in industrial and central air conditioning systems where the working temperature of R718 may vary between 280 and 298 K. Therefore, it is important to develop a thermal conductivity model which can make accurate predictions for this particular temperature range. Another motivation for this study comes from the fact that most of the research on water-based nanofluids have been conducted at elevated temperatures (above 293 K) whereas in this work, the thermal conductivity measurements were taken at a temperature as low as 280 K. The objective of the present work is to generate a regression model for the prediction of the thermal conductivity of R718-based nanofluids for low particle volume fraction scenarios. The four primary factors which are included in this analysis are thermal conductivity of nanoparticle (knp), particle volume fraction (φ), particle size (dp) and temperature (T). The thermal conductivity data available in the literature for TiO2, Al2O3 and CuO-based nanofluids were considered while generating the model. The higher particle volume fraction leads to a higher viscosity rise and higher pumping power; consequently, the model was designed for low particle volume fractions ranging from 0.25 to 1.0%.