Propriétés physiques et microstructurelles à partir d’images 3D

By using either geometric computations, direct methods or homogeneization techniques on Representative Elementary Volumes (REV) of tomographic data, it is possible to access important macroscale snow properties. Some of them are presented below.

 Porosity and density

The Porosity P and Density D can be estimated easily from a 3D Image. P is obtained directly by counting the number of voxels n belonging to the pore phase in a chosen region of interest R. Let N be the total number of voxels belonging to R. If R is sufficiently large, an estimation of P representative of the snow sample is given by the ratio n/N.
Snow density D_snow can be then obtained from the following formula :
D_snow = (1-P) x D_ice, with D_ice = 917 kg m-3.


 Main related references :


 Correlation lengths


 Main related reference :


 Specific Surface Area


 Main related references :


 Specific Grain Contact Area


 Main related reference :
  • Flin, F., B. Lesaffre, A. Dufour, L. Gillibert, A. Hasan, S. Rolland du Roscoat, S. Cabanes and P. Pugliese, 2011. On the computations of specific surface area and specific grain contact area from snow 3D images, Furukawa, Y., ed., Physics and Chemistry of Ice, Hokkaido University Press, Sapporo, Japan, 321-328. [

    pdf, 1002 kb

    ]



 Mean curvature distributions


 Main related references :


 Gaussian curvature distributions


 Main related references :


 Tensor of effective thermal conductivity


 Main related references :


 Tensor of intrinsic permeability


 Main related references :


 Tensor of diffusivity


 Main related reference :


 Tensor of tortuosity


 Main related reference :


 Minimum cut density


 Main related reference :


 Elastic stiffness tensor


 Main related reference :


Voir en ligne : Microstructure de la Neige

Portfolio