Numerical simulations of frost growth using mixture model on surfaces with different wettability

Abstract

Frost growth on cold surfaces is a transient process with coupled heat and mass transfer. Due to multiple factors such as humidity, temperature, flow velocity, and constantly changing thermal properties as frost grows, precise prediction can be challenging. Especially when the geometry of the frosting surfaces gets complicated, it requires a balance of computing accuracy and efficiency. In this work, a numerical model is developed to predict frost growth considering the effect of the above parameters. Mixture model is adapted to improve computational efficiency and the unstructured grids add the flexibility to extend the model to complex geometries. The predicted frost growth rate matches well with the experimental data reported in the literature under similar conditions. The model predicts a reasonable growth trend of frost as the surface temperature, air temperature, humidity, and flow velocity vary. The surface wettability effect is well captured at the early stage of frosting and it shows a higher frost growth rate on surfaces with a higher wettability.