Snow as a granular material: assessment of a new grain segmentation algorithm
La neige en tant que matériau granulaire : évaluation d'un nouvel algorithme de segmentation en grains
Résumé
Rapid deformations in snow are mainly con- trolled by particle rearrangements and contact interactions. To study this deformation regime, the description of the snow microstructure in terms of grains, which could eventually be handled by discrete element models, is relevant. In practice, microtomography has become a standard method to image the three-dimensional distribution of ice and pores, as a set of binary voxels. Here, we propose a new method to directly identify individual snow grains defined as zones separated by regions of potential mechanical weakness, in the microtomo- graphic images. In general, these grains are not well sepa- rated but rather sintered together. Our new method, based on local geometrical criteria, is shown to detect contacts directly inferred from an explicit numerical mechanical experiment. The developed algorithm is tested on snow but is generic and applicable to various geomaterials with a granular-like microstructure.