Experimental evaluation, sensitivity analyzation and ANN modeling of thermal conductivity of ZnO-MWCNT/EG-water hybrid nanofluid for engineering applications

Abstract

The thermal conductivity of ZnO-MWCNT / EG-water hybrid nanofluid was experimentally investigated at solid volume fractions of 0.02–1% and temperatures of 30–50°C. The thermal conductivity of a nanofluid was measured in the 50%:50% mixture of ethylene glycol (EG) and water. The results showed that the maximum thermal conductivity ratio (TCR) is obtained at 50 ˚C and at the solid volume fraction of 1%. A new correlation was proposed for prediction of experimental TCR. The coefficient of determination (R-squared) of this correlation and its maximum regression error were equal to 0.9864 and 2.6% respectively. The sensitivity measurement results showed that the hybrid nanofluid shows the highest sensitivity at the highest temperature and solid volume fraction. An artificial neural network (ANN) was developed based on the experimental TCR data. In the best case, an ANN with two hidden layers and four neurons in each layer was obtained. Comparisons of experimental TCR with ANN and correlation output indicated high capability and accuracy of ANN in modeling of TCR data.