Experimental study for thermal conductivity of water-based zirconium oxide nanofluid: Developing optimal artificial neural network and proposing new correlation

In this study, five different water based ZrO(2)nanofluids were prepared at volumetric concentrations of 0.0125%, 0.025%, 0.05%, 0.1%, and 0.2%. In the preparation of nanofluids, two-step method was preferred, magnetic stirrer and ultrasonic homogenizer were used. Their thermal conductivity was measured experimentally in the temperature range of 10 degrees C to 65 degrees C. Using the obtained experimental data, a multi-layer perceptron feed-forward back-propagation artificial neural network was developed. In addition, a new correlation was proposed for the calculation of the thermal conductivity values of the ZrO2/Water nanofluid. The results showed that the ZrO2/Water nanofluid had higher thermal conductivity compared to the base fluid and the thermal conductivity increases with the increase in temperature and concentration. While the artificial neural network developed with experimental data predicted the thermal conductivity of ZrO2/Water nanofluid with an average error of -0.41%, the new correlation developed predicted it with an average error of -0.02%. These values were an indication that the results obtained from the developed artificial neural network and the correlation are in perfect agreement with the experimental data.

Automated summary

In this study, five different water-based ZrO(2)nanofluids were prepared at different concentrations, and their thermal conductivity was experimentally measured. Using the data obtained, an artificial neural network and a new correlation were developed to predict the thermal conductivity values, showing perfect agreement with the experimental data.