Experimental study of bubble growth on novel fin structures during pool boiling

Abstract

Boiling heat transfer associated with phase change is perhaps one of the most efficient cooling methodologies to manage extreme heat flux due to its large latent heat. Fin structures are used to further increase the magnitude of boiling heat transfer from the heated surface and have shown better performance than flat surface heat sinks. This work aims to experimentally investigate the heat transfer performance of two fin structures, namely regular and modified fins, in a pool boiling facility. The modified hollow fin structure is designed to enhance the regular fin's heat transfer performance by adding an artificial nucleation site. Heat transfer rates and heat transfer coefficients of the two fin structures are estimated in atmospheric pressure conditions using deionized water and compared with the literature. The results show that the regular fin heat sink shows a better heat transfer rate than the plane surface, while the modified fin structure shows higher heat transfer performance than the regular fin. This is attributed to the additional nucleation sites on the hollow fin, a better rewetting phenomenon, and therefore a favorable bubble growth and release mechanism. Also, a multilayer perceptron artificial neural network with a back-propagation training algorithm is applied for modeling the bubble departure diameter concerning wall superheat and subcooling level to predict the bubble behavior from the artificial nucleation site.