A frost model based on the frost layer's supporting function. (March 2023)

• Record Type: Journal Article
• Authors: Xu, Zhiming; Wang, Zhanpeng; Liang, Zhen; Chen, Hongtu; Han, Zhimin
• Is Part Of: International journal of heat and mass transfer. Volume 202(2023)
• Publication Date: 2023-03
• Subjects: Frost formation and growth -- Numerical simulation -- Supporting function -- Heat and mass transfer; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2022.123741
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: A new frosting model based on the supporting function of frost layer is proposed. Using the ice phase volume fraction threshold to represent the supporting capacity of the frost layer. The threshold is proportional to the change of frost thickness, density, temperature and wet air velocity. Compared with the related experimental data, the average error of frost thickness and density were 4.9% and 5.5%, respectively. Abstract: The existence of frost has adverse effects the normal operation of air source heat pumps. Therefore, establishing an accurate frost model is of great significance to suppressing the formation of frost layers on cold surfaces. Since the frost layer grows gradually and cumulatively layer by layer in the actual physical frosting process, it is important to consider the supporting function of the lower frost layer in the process. This study proposes the use of the ice volume fraction threshold of the frost layer to determine whether the supporting condition is satisfied, in addition to using the threshold to determine the occurrence of frosting. A new frost model is developed with the given volume fraction threshold fitting formula. In order to verify the accuracy of the proposed model, the simulation results were compared with 17 groups of experimental results from four representative experiments. It was found that the simulation results of this model were in good agreement with the experimental data, and the average error of thickness did not exceed 4.9%, while the average error of density was less than 5.5%.