Simulation of discharging by loading various sizes of nano-powders utilizing numerical method for analyzing unsteady heat transfer

The present study focuses on enhancing cold storage efficiency by introducing alumina nano-powders into water within a uniquely designed container. The governing model prioritizes the conduction mode as the primary driving force for the freezing process. To simulate this complex phenomenon, we employ a combination of the adaptive mesh and Galerkin method, utilizing a homogeneous mixture to mimic nanomaterial behavior. The diverse shapes of the dispersed powders are shown to influence system behavior, as detailed in the presented outputs. The investigation specifically considers two crucial variables: concentration (phi) and shape factor (m). Additionally, the adaptive grid adjusts according to the ice front's position. The results demonstrate a significant reduction in freezing time by approximately 45.94% with an increase in phi. Furthermore, selecting particles with a higher "m" value leads to a 9.68% decrease in the required time.