Transient heat transfer analysis of phase change material melting in metal foam by experimental study and artificial neural network

Abstract

Phase change material with porous media (PCM-porous) is an efficient and promising thermal management system for an electronic or photovoltaic system that needs heat dissipation or preservation. Studying the transient heat transfer process of the PCM-porous system is conducive to understand the main effect factors that influence its working process and the differences in its melting process between the pure PCM. The lab-based experiment coupled with the artificial neural network (ANN) method is used to study the transient heat transfer process of the PCM-porous system. The experimental results show that the porosity of metal foam has a greater influence on the melting and heat transfer of PCM than the pore density. The experimental data are used to train the ANN model, which predicts the parameters of the PCM-porous system during the heat transfer process, including the liquid fraction, temperature, and average Nusselt number based on time and the porosity of metal foam. Moreover, a classification ANN model is developed to predict the porosity of metal foam based on the liquid fraction, temperature, average Nusselt number. This study provides a reference to choose the porosity of the PCM-porous system for designers and proposes a novel way to explore the heat transfer process of the PCM-porous system.