Modelling Thermal Conductivity of Oxide Nanofluids

Abstract

Suspension of nano-sized particles in a base fluid (commonly known as “nanofluids”) has come up in recent years as a potential heat transfer media primarily because of its improved thermal characteristics (such as thermal conductivity). In spite of its potential wide industrial application (such as in electronics, refrigeration, automobile sectors), only limited progress has been made so far towards developing a reliable model to predict important design parameter such as thermal conductivity. This thesis work presents results of an ongoing investigation into the modelling of thermal conductivity for Alumina-Water and Titanium oxide-Water nanofluids. In spite of having the promise of being an improved heat transfer medium, fundamental understanding and modelling of important thermo-physical properties of nanofluids (such as thermal conductivity) have remained a difficult task due to the possible influence of several particle and base fluid properties on the behaviour of nanofluids. Some existing theoretical and empirical models for thermal conductivity of nanofluids have been evaluated for their accuracy by comparing the predicted versus experimental data for a wide range of test conditions. The existing models are found to provide inaccuracies (over/under-predictions) within the range of 2-47%. A new model has been developed using dimensionless analysis, which includes Prandtl number and a new dimensionless number that is a ratio to Reynolds number to the square root of Brinkman number for particle and fluids. The new model has been found to generally predict the thermal conductivity ratio (nanofluids to base fluids) within 5% accuracy range for Al2O3-water naofluids and 6% accuracy range for TiO2-water nanofluids.