Effect of loading nanoparticles on thermodynamic behavior of water during freezing within storage tank

Abstract

In this paper, the simulation of freezing within a cold storage unit is undertaken, featuring a container equipped with distinctive branch-shaped fins attached to the lower cold surface. The primary mode of freezing is conduction, causing the simplification of governing equations and resulting in two key equations. The Galerkin method is employed for numerical modeling, accompanied by an adaptive grid for enhanced accuracy. Unsteady terms are discretized using implicit formulation, and the resulting numerical procedure is rigorously validated against benchmarks, revealing commendable accuracy. To enhance cold storage efficiency, a dual approach is introduced, extending beyond conventional fin applications to include nanoparticles dispersed within the water. This approach significantly amplifies the system’s performance by enhancing the conduction mode of heat transfer. Two pivotal variables, the volume fraction ([Formula: see text]) of the nanofluid and its shape factor (m), are central to the investigation. Notably, the presence of nanoparticles results in a minimum freezing period of 8.08[Formula: see text]s, while the longest process takes 11.6[Formula: see text]s. Further exploration reveals that an increase in both m and [Formula: see text] correlates with a notable decrease in the freezing period, reducing by 9.97% and 30.33%, respectively. This study advances understanding of cold storage dynamics and introduces innovative methods for optimizing efficiency. The strategic use of branch-shaped fins and the incorporation of nanoparticles represent crucial breakthroughs in heat transfer. The findings underscore the importance of considering these factors for optimal performance, making this study a pivotal contribution to cold storage technology.