Experimental Study for Thermophysical Properties of ZrO2/Ethylene Glycol Nanofluid: Developing an ANFIS Modeling and Proposing New Correlations

Abstract

Nanofluids are potential coolants for heat transfer applications because of their excellent thermal characteristics. Experimentally the thermophysical properties of ZrO2/ethylene glycol nanofluids are determined at 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% vol. concentrations. A two-step method is used to prepare the stable nanofluids. The ZrO2/EG nanofluids properties were estimated over temperature ranging from 20 °C to 60 °C. From the experimental data, a multi-layer perceptron feed-forward back propagation artificial neural network was developed. Additionally, new correlations were proposed for all the thermophysical properties. The experimental analysis showed that thermal conductivity is enhanced by 19.6% at 60 °C and viscosity is enhanced by 86.62% at 20 °C at 1.0% vol. of nanofluid, density is enhanced by 4.9%, and specific heat is decreased by 4.2% at 1.0% vol. of nanofluid and at 60 °C, over base fluid data. The proposed ANN model succeeded in predicting the target property with minimum RMSE. The results of the developed artificial neural network and its correlation analysis perfectly agree with the experimental data.