摘要

In This research study, the thermal conductivity of Al₂O₃ nanoparticles dispersed in different base fluid (Water, EG and Transformer Oil) is studied for different temperatures and weight fractions using bagging with artificial neural network (ANN) and experimental data. For the purpose of training the ANN, the thermal conductivity of nanofluid is measured in temperatures between 20 and 50 °C and volume fractions equal to 0.1, 0.5, 1.0, 2.0 and 3.0. For the purpose of evaluating the accuracy of the proposed model by ANN, root mean square error (RMSE) and mean absolute percentage error (MAPE) are utilized. The inputs of the ANN model are weight fraction and nanofluid temperature and the output of the network is the thermal conductivity of the nanofluid. The result indicates that the proposed model by ANN can precisely predict the thermal conductivity of the nanofluids.