Experimental and numerical data of vacuum freezing of food products

The aim of this study was to develop a validated numerical model of vacuum freezing for various food products. Effective precooling or prefreezing is crucial for preserving food quality and safety during multistep transport. The developed CFD model describes heat and mass transfer during the entire vacuum freezing process of various food products, including the phase change stage. To model supercooling and nucleation phenomena during freezing, apparent specific heat was introduced at the initial freezing temperature, demonstrating a temperature plateau during the phase transition of the simulation. The model was validated using an experimental test rig designed for vacuum freezing and storing small batches of food products. Compared with the experimental data, the accuracy of the temperature predicted via the model, as evaluated by the relative root mean square error, was 8.1%. The validated model was then used to predict the temperature profiles of three fruits that had the same shape but differed in composition, as well as in their physical and thermal properties. The results show that food products with higher permeability freeze significantly faster than foods with lower permeability. Moreover, the effects of the surface-to-volume ratio on the process efficiency for three different shapes of mango were investigated via vacuum freezing. The study revealed that a shape with a 36% greater surface-to-volume ratio, compared with another shape of the same volume, reduced the vacuum freezing time by 50%. Furthermore, the impact of the pumping speed on the effectiveness of vacuum freezing was evaluated. The results revealed that increasing the pumping speed by a factor of ten improved the cooling and freezing time by only 13%.