Numerical modeling of physical behavior of PCM in attendance of nano-sized additives

Abstract

In this paper, freezing through a cold storage unit is simulated, featuring a container equipped with branch-shaped fins attached to the lower cold surface. Conduction emerges as the primary influencer of the freezing process, leading to the simplification of governing equations and the adoption of the Galerkin method for numerical modeling. Notably, an adaptive grid is introduced to enhance accuracy, and the discretization of unsteady terms is achieved through implicit formulation. Rigorous validation against benchmark data attests to the reasonable accuracy of the numerical procedure. Innovatively, to enhance the efficiency of cold storage, nanoparticles are dispersed within the water, in addition to the strategic use of fins. Both methods contribute to enhancing the system’s performance by amplifying the conduction mode of heat transfer. Two key variables are considered: the volume fraction ([Formula: see text]) of the nanofluid and its shape factor (m). The study reveals that increasing [Formula: see text] and m results in a lower period of freezing, showing reductions of approximately 1.81% and 17.59%, respectively.