Tomography-based determination of porosity, specific area and permeability of snow and comparison with measurements

Micro-computed tomography (μ-CT) of snow replicas is used to characterize 34 snow samples by determining their specific surface area, porosity, effective permeability, anisotropy, and tortuosity. Their 3D geometrical representation obtained by μ-CT is used in direct pore-level simulations (DPLS) to numerically solve the governing mass and momentum conservation equations for fluid flow through porous media. It is found that inertial effects, given by a second and third order correction in Darcyʹs law, influence the air flow even at low Reynolds numbers. Correlations are derived for permeability, the Dupuit–Forchheimer coefficient and the third order coefficient of Darcyʹs law as a function of density and grain size. Comparison with the experimentally measured data yields good agreement and confirms the applicability of DPLS for determining the transport properties of snow.