Neural network analysis of boiling heat transfer enhancement using additives

A model was developed to evaluate and predict boiling heat transfer enhancement using additives. The model is based on the molecular structures of the additives and uses artificial neural network technology. The effects of 30 additives tested by the authors and other researchers on the augmentation of boiling heat transfer were analyzed with the model. The results show that the evaluation of all 30 additives is consistent with the experimental data, which means that the training accuracy of the model is 100%. In addition, the boiling heat transfer enhancement with sodium oleate and 11 other additives was also predicted, with a prediction accuracy of over 90% since the calculated results for 10 of the 11 additives were in agreement with the experimental results.