Prediction of heat transfer characteristics of nanofluids in heat pipes based on artificial neural network model

Abstract

The objective of this study is to predict the heat transfer characteristics of nanofluids in heat pipes based on artificial neural network (ANN) theory. A visualized experiment for analyzing the heat transfer performance of heat pipes with nanofluid was constructed, and the effects of heating capacity, inclination angle, pipe diameter, nanofluid concentration and particle suspendability on the heat transfer characteristic of heat pipe were analysed. The heat transfer characteristics of nanofluids in heat pipes were contrasted with that of the heat pipe containing the base fluid only. This ANN model had been proven to be desirable in accuracy for predicting the heat transfer characteristics of heat pipe using nanofluid by comparing ANN model results with experimental results at the same operating conditions. This work provides an accurate modeling approach based on ANN for the research of heat transfer characteristics of nanofluids in heat pipes and solving phase change heat transfer problems related with complicated condition.