  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 the 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 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.
