Modeling of thermal conductivity of ZnO-EG using experimental data and ANN methods

• Main Authors: Esfe, Mohammad Hemmat, Saedodin, Seyfolah, Naderi, Ali, Alirezaie, Ali, Karimipour, Arash, Wongwises, Somchai, Goodarzi, Marjan, Dahari, Mahidzal
• Format: Article
• Language: English
• Published: Elsevier 2015
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/15692/1/Modeling_of_thermal_conductivity_of_ZnO-EG_using_experimental_data.pdf; http://eprints.um.edu.my/15692/; https://doi.org/10.1016/j.icheatmasstransfer.2015.01.001

In the present study, the thermal conductivity of the ZnO-EG nanofluid has been investigated experimentally. For this purpose, zinc oxide nanoparticles with nominal diameters of 18 nm have been dispersed in ethylene glychol at different volume fractions (0.000625, 0.00125, 0.005, 0.01, 0.015, 0.02, 0.03, 0.04, and 0.05) and temperatures (24-50 degrees C). The two-step method is used to disperse nanoparticles in the base fluid. Based on the experimental data, an experimental model has been proposed as a function of solid concentration and temperature. Then, the feedforward multilayer perceptron neural network has been employed for modeling thermal conductivity of ZnO-EG nanofluid. Out of 40 measured data obtained from experiments, 28 data were selected for network training, while the remaining 12 data were used for network testing and validating. The results indicate that both model and ANN outputs are in good agreement with the experimental data. (C) 2015 Elsevier Ltd. All rights reserved.