CFD aided cognitive capabilities for analyzing snowdrift development around a porous fence

Physical experimental investigations of snowdrift development around structures are often associated high costs with equipment, labor, time and accessibility. Computational Fluid Dynamics technique creates a CogInfoCom channel in a way to improve human cognitive abilities. This paper presents a 2D homogeneous mixture Eulerian-Eulerian model to simulate snowdrift development around the Wyoming snow fence with its porosity of 0.50. The model allows assessing and visualizing of snowdrift development through a domain adaption strategy for the transient changes in snow surface topography. The simulation results are quantitatively in good agreement with the field observations.