Investigation of nano-particle effects on cold storage performance using finite element modeling

This work examines the optimization of additive materials to enhance the solidification rate in a cold energy storage system equipped with a finned enclosure. Nanometer-scale particles were dispersed into the water-based medium to promote faster freezing. The system performance was evaluated by numerically investigating different nanoparticle volume fractions and particle diameters to assess their effects on the solidification process. The governing equations were solved using the Galerkin finite element approach, and the numerical predictions showed strong agreement with available experimental observations. An adaptive meshing strategy was applied to accurately resolve the transient characteristics of the freezing front. In contrast to earlier investigations that primarily examined the influence of nanoparticle concentration or storage unit configuration, the present work provides a systematic numerical assessment of the combined influence of nanoparticle diameter and concentration on the solidification characteristics of a finned cold energy storage system. An adaptive Galerkin finite element framework is employed to accurately capture the transient evolution of the freezing front and identify optimal nanoparticle conditions for enhanced thermal storage performance. The results indicate that selecting an optimal nanoparticle size significantly improves freezing performance, with a 20% increase in the solidification rate. Furthermore, the dispersing nanoparticles shortened the total freezing duration by about 41.23%, highlighting their effectiveness in enhancing the thermal performance of the storage system.