Abstract
Improving the performance of storage units is important for saving energy. An implicit approach has been combined with the adaptive grid in this modelling for the presentation of solidification inside the tank with a sinusoidal cold surface. Not only the implementation of curved will but also the inclusion of nanoparticles was assumed as a passive technique for expediting freezing. The scalars were extracted by the Galerkin approach. The formulation of nanomaterial features was done by considering uniform concentration inside the domain. Increasing the fraction of CuO can reduce the freezing time from 2211.13 to 1943.72 s and 1675.37 s if the blade shape is selected. The augmentation of shape factor and fraction of nanomaterial lead to the reduction of freezing time by about 6.98% and 24.23%, respectively. The results proved that ϕ has a stronger effect than other active parameters.