Mapping of density-dependent material properties of dry manufactured snow using μCT

Despite the significance of snow in various cryospheric, polar, and construction contexts, more comprehensive studies are required on its mechanical properties. In recent years, the utilization of μ CT has yielded valuable insights into snow analysis. Our objective is to establish a methodology for mapping density-dependent material properties for dry manufactured snow within the density range of 400–600 kg/m 3 utilizing μ CT imaging and step-wise, quasi-static, mechanical loading. We also aim to investigate the variations in the structural parameters of snow during loading. The three-dimensional (3D) structure of snow is captured using μ CT with 801 projections at the beginning of the experiments and at the end of each loading step. The sample is compressed at a temperature of − 18 o C using a constant rate of deformation (0.2 mm/min) in multiple steps. The relative density of the snow is determined at each load step using binary image segmentation. It varies from 0.44 in the beginning to nearly 0.65 at the end of the loading, which corresponds to a density range of 400–600 kg/m 3 . The estimated modulus and viscosity terms, obtained from the Burger’s model, show an increasing trend with density. The values of the Maxwell and Kelvin–Voigt moduli were found to range from 60 to 320 MPa and from 6 to 40 MPa, respectively. Meanwhile, the viscosity values for the Maxwell and Kelvin–Voigt models varied from 0.4 to 3.5 GPa-s, and 0.3–3.2 GPa-s, respectively, within the considered density range. In addition, Digital Volume Correlation (DVC) was used to calculate the full-field strain distribution in the specimen at each load step. The image analysis results show that, the particle size and specific surface area (SSA) do not change significantly within the studied range of loading and densities, while the sphericity of the particles is increased. The grain diameter ranges from approximately 100 μ m to nearly 400 μ m, with a mode of nearly 200 μ m. The methodology presented in this study opens up a path for an extensive statistical analysis of the material properties by experimenting more snow samples.Full text license: CC BY