Enhancing cold energy storage in finned enclosures with nanoparticles involving transient conduction

Abstract

This study presents a detailed numerical modeling of the freezing within a cold storage unit enhanced by the incorporation of fins and CuO nanoparticles. The presence of fins meaningfully improves the thermal efficiency of the unit, while the addition of nano-powders further accelerates the solidification. Various concentrations (ϕ) and diameters (dp) were considered to evaluate their impact on the solidification rate. The mathematical model for this process was developed under two key assumptions: that the thermophysical properties could be accurately predicted using a homogeneous mixture model and that convective effects within the system were negligible. The FEM molding's accuracy was confirmed through rigorous verification tests. One of the novel aspects of this study is the adaptive grid configuration, which evolves over time to accurately track the advancing ice front during the freezing process. The results indicated that the introduction of CuO nano-powders led to a substantial decrement in the completion time about 41.59 %. In the optimal scenario, full freezing was achieved in just 131.56 s, compared to 225.27 s for the base case with water alone. Additionally, the study found that the performance of the cold storage unit was highly dependent on the size of the nanoparticles. An intermediate nanoparticle diameter provided the best performance, with a 19.93 % reduction in freezing time initially observed as dp increased.

Keywords

• Size of additives
• Energy storage
• Freezing process
• Unsteady conduction
• Numerical simulation
• Nanomaterial