Modeling the freezing of nanomaterial through the cold storage unit implementing numerical approach

Abstract

In this attempt, the freezing period in the system was effectively reduced by introducing a fin and incorporating nanoparticles. The attachment of a fin to a vertical cold surface, coupled with an insulated tilted wall, strategically optimized the freezing process. Both the concentration of CuO nano-powders and the sizes of the additives were meticulously examined in the modeling, emphasizing their roles in enhancing the conduction mode. The proposed model, derived through the approximation of the homogeneous model and deliberately neglecting velocity terms, was solved using the Galerkin method and validated against previous data. Size variations from dp = 40 to 50 nm resulted in a notable 49.3 % increase in freezing time, while changes from 30 to 40 nm led to a 20.01 % reduction. Furthermore, the dispersion of CuO nanoparticles with ϕ = 0.02 significantly improved solidification by approximately 27.06 %. These findings offer valuable insights for practical applications, showcasing the potential of this approach to optimize freezing processes in diverse systems.