Thermal analysis of cold saving system via numerical modeling incorporating nanomaterial

Abstract

Current article presents a numerical modeling of the discharging process within a finned tank using the Galerkin method integrated with an implicit technique. The model dynamically adapts the grid configuration to the position of the solidification front, ensuring precise capture of the unsteady process. To enhance the freezing rate, alumina nanoparticles of various diameters (dp) and concentrations (ϕ) were introduced into the water. The properties of the nanocomposite material were estimated assuming a homogeneous mixture, with conduction considered the primary mechanism of heat transfer. The results demonstrate that increasing the (ϕ) significantly accelerates the solidification, reducing the required time by 41.31%, from 9579.68 to 5621.78 s. The study also reveals a complex relationship between nanoparticle diameter (dp) and freezing time, where initial increases in dp reduce the freezing period by 20%, followed by an increase of 48.38% with further increases in dp.