Experimental Investigation and Modeling of Bubble Departure Frequency for Pool‐Boiling Heat Transfer

Abstract

The artificial neural network (ANN) method and response surface methodology (RSM) were used to predict the bubble departure frequency for the pool-boiling heat transfer of pure liquids, by using experimental data. The effects of vaporliquid density difference, vapor-liquid viscosity difference, surface tension, thermal conductivity, and heat flux on the departure frequency of vapor bubbles were investigated by RSM and ANN. The results showed that the outputs of the ANN and RSM had a suitable overlap with the experimental data, but the RSM model was more accurate than the ANN model.