Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3787-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-3787-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2024
Research article |
| 23 Aug 2024
| 23 Aug 2024
Microstructure-based modelling of snow mechanics: experimental evaluation of the cone penetration test
Clémence Herny
CORRESPONDING AUTHOR
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
IGE, Univ. Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, Grenoble, France
Pascal Hagenmuller
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
Guillaume Chambon
IGE, Univ. Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, Grenoble, France
Isabel Peinke
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
Jacques Roulle
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
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The thermal conductivity of snow is an important physical property governing the thermal regime of a snowpack and its substrate. We show that it strongly depends on the kinetics of water vapor sublimation and that previous experimental data suggest a rather fast kinetics. In such a case, neglecting water vapor leads to an underestimation of thermal conductivity by up to 50 % for light snow. Moreover, the diffusivity of water vapor in snow is then directly related to the thermal conductivity.
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There has been a long controversy to determine whether the effective diffusion coefficient of water vapor in snow is superior to that in free air. Using theory and numerical modeling, we show that while water vapor diffuses more than inert gases thanks to its interaction with the ice, the effective diffusion coefficient of water vapor in snow remains inferior to that in free air. This suggests that other transport mechanisms are responsible for the large vapor fluxes observed in some snowpacks.
Cited articles
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I—Numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002.
Bishop, R. F., Hill, R., and Mott, F. N.: The theory of indentation hardness tests, P. Phys. Soc., 57, 321, https://doi.org/10.1088/0959-5309/57/3/301, 1945.
Bobillier, G., Bergfeld, B., Capelli, A., Dual, J., Gaume, J., van Herwijnen, A., and Schweizer, J.: Micromechanical modeling of snow failure, The Cryosphere, 14, 39–49, https://doi.org/10.5194/tc-14-39-2020, 2020.
Bobillier, G., Bergfeld, B., Dual, J., Gaume, J., Herwijnen, A., and Schweizer, J.: Micro-mechanical insights into the dynamics of crack propagation in snow fracture experiments, Sci. Rep.-UK, 11, 11711, https://doi.org/10.1038/s41598-021-90910-3, 2021.
Bolton, M. D., Gui, M. W., and Phillips, R.: Review of miniature soil probes for model tests, in: Proceedings of the 11th Southeast Asian Geotechnical Conference, Singapore, 4–8 May 1993, 85–90, 1993.
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992.
Calonne, N., Flin, F., Geindreau, C., Lesaffre, B., and Rolland du Roscoat, S.: Study of a temperature gradient metamorphism of snow from 3-D images: time evolution of microstructures, physical properties and their associated anisotropy, The Cryosphere, 8, 2255–2274, https://doi.org/10.5194/tc-8-2255-2014, 2014.
Calonne, N., Flin, F., Lesaffre, B., Dufour, A., Roulle, J., Puglièse, P., Philip, A., Lahoucine, F., Geindreau, C., Panel, J.-M., Rolland du Roscoat, S., and Charrier, P.: CellDyM: a room temperature operating cryogenic cell for the dynamic monitoring of snow metamorphism by time-lapse X-ray microtomography, Geophys. Res. Lett., 42, 3911–3918, https://doi.org/10.1002/2015GL063541, 2015.
Coeurjolly, D., Montanvert, A., and Chassery, J.-M.: Descripteurs de forme et moments géométriques, in: Géométrie discrète et images numériques, Hermès, ISBN13 978-2-7462-1643-3, EAN13 9782746216433, https://www.eyrolles.com/Informatique/Livre/geometrie-discrete-et-images-numeriques-9782746216433/ (last access: 19 August 2024), 2007.
Coléou, C., Lesaffre, B., Brzoska, J.-B., Ludwig, W., and Boller, E.: Three dimensional snow images by X-ray microtomography, Ann. Glaciol., 32, 75–81, https://doi.org/10.3189/172756401781819418, 2001.
De Pue, J., Di Emidio, G., Verastegui Flores, R. D., Bezuijen, A., and Cornelis, W. M.: Calibration of DEM material parameters to stimulate stress-strain behaviour of unsaturated soils during uniaxial compression, Soil Till. Res., 194, 104303, https://doi.org/10.1016/j.still.2019.104303, 2019.
Dowd, T. and Brown, R. L.: A new instrument for determining strength profiles in snow cover, J. Glaciol., 32, 299–301, https://doi.org/10.3189/S0022143000015628, 1986.
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., and McClung, D. M.: The international classification for seasonal snow on the ground, in: Tech. Doc. Hydrol. 83, UNESCO, Paris, 2009.
Fish, A. M. and Zaretsky, Y. K.: Ice strength as a function of hydrostatic pressure and temperature, CRREL report, 38207814, Cold Regions Research and Engineering Laboratory, https://books.google.ch/books/about/Ice_Strength_as_a_Function_of_Hydrostati.html?id=smZ-0AEACAAJ&redir_esc=y (last access: 19 August 2024), 1997.
Floyer, J. A. and Jamieson, J. B.: Rate-effect experiments on round-tipped penetrometer insertion into uniform snow, J. Glaciol., 56, 664–672, https://doi.org/10.3189/002214310793146322, 2010.
Freitag, J., Wilhelms, F., and Kipfstuhl, S.: Microstructure dependent densification of polar firn derived from X-ray microtomography, J. Glaciol., 50, 243–250, https://doi.org/10.3189/172756504781830123, 2004.
Gammon, P. H., Kiefte; H., Clouter, M. J., and Denner, W. W.: Elastic constants of artificial and natural ice samples by Brillouin spectroscopy, J. Glaciol., 29, 433–460, https://doi.org/10.3189/S0022143000030355, 1983.
Gaume, J., van Herwijnen, A., Chambon, G., Birkeland, K. W., and Schweizer, J.: Modeling of crack propagation in weak snowpack layers using the discrete element method, The Cryosphere, 9, 1915–1932, https://doi.org/10.5194/tc-9-1915-2015, 2015.
Gaume, J., van Herwijnen, A., Chambon, G., Wever, N., and Schweizer, J.: Snow fracture in relation to slab avalanche release: critical state for the onset of crack propagation, The Cryosphere, 11, 217–228, https://doi.org/10.5194/tc-11-217-2017, 2017a.
Gaume, J., Löwe, H., Tan, S., and Tsang, L.: Sacaling laws for the mechanics of loose and cohesive granular materials based on Baxter's sticky hard spheres, Phys. Rev. E, 96, 032914, https://doi.org/10.1103/PhysRevE.96.032914, 2017b.
Gubler, H. U.: On the ramsonde hardness equation, IAHS-AISH Publ., 114, 110–121, 1975.
Hagenmuller, P., Chambon, G., Lesaffre, B., Flin, F., and Naaim, M.: Energy-based binary segmentation of snow microtomographic images, J. Glaciol., 59, 859–873, https://doi.org/10.3189/2013JoG13J035, 2013.
Hagenmuller, P., Calonne, N., Chambon, G., Flin, F., Geindreau, C., and Naaim, M.: Characterization of the snow microstructural bonding system through the minimum cut density, Cold Reg. Sci. Technol., 108, 72–79, https://doi.org/10.1016/j.coldregions.2014.09.002, 2014.
Hagenmuller, P., Chambon, G., and Naaim, M.: Microstructure-based modeling of snow mechanics: a discrete element approach, The Cryosphere, 9, 1969–1982, https://doi.org/10.5194/tc-9-1969-2015, 2015.
Heggli, M., Köchle, B., Matzl, M., Pinzer, B. R., Riche, F., Steiner, S., Steinfeld, D., and Schneebeli, M.: Measuring snow in 3-D using X-ray tomography: Assessment of visualization techniques, Ann. Glaciol., 52, 231–236, https://doi.org/10.3189/172756411797252202, 2011.
Herwijnen, A. V.: Experimental analysis of snow micropenetrometer (SMP) cone penetration in homogeneous snow layers, Can. Geotech. J., 50, 1044–1054, https://doi.org/10.1139/cgj-2012-0336, 2013.
Jamieson, J. B. and Johnston, C. D.: Snowpack characteristics associated with avalanche accidents, Can. Geotech. J., 29, 862–866, https://doi.org/10.1139/t92-093, 1992.
Johnson, J. and Schneebeli, M.: Characterizing the microstructural and microchemical properties of snow, Cold Reg. Sci. Technol., 30, 91–100, https://doi.org/10.1016/S0165-232X(99)00013-0, 1999.
Johnson, J. B. and Hopkins, M. A.: Identifying microstructural deformation mechanisms in snow using discrete-element modeling, J. Glaciol., 51, 432–442, https://doi.org/10.3189/172756505781829188, 2005.
LeBaron, A., Miller, D., and van Herwijnen, A.: Measurements of the deformation zone around a split-axis snow micropenetrometer tip, Cold Reg. Sci. Technol., 97, 90–96, https://doi.org/10.1016/j.coldregions.2013.10.008, 2014.
Löwe, H. and van Herwijnen, A.: A Poisson shot noise model for micropenetration of snow, Cold Reg. Sci. Technol., 70: 62–70, https://doi.org/10.1016/j.coldregions.2011.09.001, 2012.
Lunne, T., Robertson, P. K., and Powell, J. J. M.: Cone penetration testing in geotechnical practice, Blackie Academic, EF Spon/Routledge, New York, 1997.
Mackenzie, R. and Payten, W.: A portable, variable-speed, penetrometer for snow pit evaluation, in: Proceedings of the 2002 International Snow Science Workshop, Penticton, BC, 29 September–4 October 2002, 294–300, 2002.
Maeno, N. and Arakawa, M.: Adhesion shear theory of ice friction at low sliding velocities, combined with ice sintering, J. Appl. Phys., 95, 134–139, https://doi.org/10.1063/1.1633654, 2004.
Marshall, H. P. and Johnson, J. B.: Accurate inversion of high-resolution snow penetrometer signals for microstructural and micromechanical properties, J. Geophys. Res.-Earth, 114, F04016, https://doi.org/10.1029/2009JF001269, 2009.
McCallum, A.: A brief introduction to cone penetration testing (CPT) in frozen geomaterials, Ann. Glaciol., 55, 7–14, https://doi.org/10.3189/2014AoG68A005, 2014.
Mede, T., Chambon, G., Hagenmuller, P., and Nicot, F.: A medial axis based method for irregular grain shape representation in DEM simulations, Granul. Matter, 20, 1–11, https://doi.org/10.1007/s10035-017-0785-7, 2018a.
Mede, T., Chambon, G., Hagenmuller, P., and Nicot, F.: Snow failure modes under mixed loading, Geophys. Res. Lett., 45, 13–351, https://doi.org/10.1029/2018GL080637, 2018b.
Mede, T.: Etude numérique du comportement mécanique de la neige: une perspective microstructurale, Université Grenoble Alpes, https://theses.fr/2019GREAU004 (last access: 19 August 2024), 2019.
Mede, T., Chambon, G., Nicot, F., and Hagenmuller, P.: Micromechanical investigation of snow failure under mixed-mode loading, Int. J. Solids Struct., 199, 95–108, https://doi.org/10.1016/j.ijsolstr.2020.04.020, 2020.
Montagnat, M., Löwe, H., Calonne, N., Schneebeli, M., Matzl, M., and Jaggi, M.: On the birth of structural and crystallographic fabric signals in polar snow: A case study from the EastGRIP snowpack, Front. Earth Sci., 8, 365, https://doi.org/10.3389/feart.2020.00365, 2020.
Narita, H.: An experimental study on tensile fracture of snow, Contribut. Inst. Low Temperat. Sci., A32, 1–37, 1983.
Peinke, I.: Étude à micro-échelle du test de pénétration du cône dans la neige, Météorologie, Université Paul Sabatier – Toulouse III, https://theses.hal.science/tel-02879065v1/document (last access: 19 August 2024), 2019.
Peinke, I., Hagenmuller, P., Chambon, G., and Roulle, J.: Investigation of snow sintering at microstructural scale from micro-penetration tests, Cold Reg. Sci. Technol., 162, 43–55, https://doi.org/10.1016/j.coldregions.2019.03.018, 2019.
Peinke, I., Hagenmuller, P., Andò, E., Chambon, G., Flin, F., and Roulle, J.: Experimental Study of Cone Penetration in Snow Using X-Ray Tomography, Front. Earth Sci., 8, 63, https://doi.org/10.3389/feart.2020.00063, 2020.
Proksch, M., Löwe, H., and Schneebeli, M.: Density, specific surface area, and correlation length of snow measured by high-resolution penetrometry, J. Geophys. Res.-Earth, 120, 346–362, https://doi.org/10.1002/2014JF003266, 2015.
Reuter, B., Proksch, M., Löwe, H., Van Herwijnen, A., and Schweizer, J.: Comparing measurements of snow mechanical properties relevant for slab avalanche release, J. Glaciol., 65, 55–67, https://doi.org/10.1017/jog.2018.93, 2019.
Ruiz, S., Straub, I., Schymanski, S. J., and Or, D.: Experimental evaluation of earthworm and plant root soil penetration-cavity expansion models using cone penetrometer analogs, Vadose Zone J., 15, 1–14, https://doi.org/10.2136/vzj2015.09.0126, 2016.
Ruiz, S., Capelli, A., van Herwijnen, A., Schneebeli, M., and Or, D.: Continuum cavity expansion and discrete micromechanical models for inferring macroscopic snow mechanical properties fromcone penetration data, Geophys. Res. Lett., 44, 8377–8386, https://doi.org/10.1002/2017GL074063, 2017.
Shapiro, L. H., Johnson, J. B., Sturm, M., and Blaisdell, G. L.: Snow mechanics: review of the state of knowledge and applications, CRREL Rep. 97-3, Cold Regions Research and Engineering Laboratory, https://apps.dtic.mil/sti/citations/ADA330695 (last access: 19 August 2024), 1997.
Schaap, L. H. J. and Föhn, P. M. B.: Cone penetration testing in snow, Can. Geotech. J., 24, 335–341, https://doi.org/10.1139/t87-044, 1987.
Schneebeli, M.: Numerical simulation of elastic stress in the microstructure of snow, Ann. Glaciol., 38, 339–342, https://doi.org/10.3189/172756404781815284, 2004.
Schneebeli, M. and Johnson, J. B.: A constant-speed penetrometer for high resolution snow stratigraphy, Ann. Glaciol., 26, 107–111, https://doi.org/10.3189/1998AoG26-1-107-111, 1998.
Schneebeli, M. and Sokratov. S. A.: Tomography of temperature gradient metamorphism of snow and associated changes in heat conductivity, Hydrol. Process., 18, 3655–3665, https://doi.org/10.1002/hyp.5800, 2004.
Schulson, E. M. and Duval, P.: Creep and Fracture of Ice, Cambridge University Press, ISBN 978-0-521-80620-6, 2009.
Schweizer, J., Jamieson, J. B., and Schneebeli, M.: Snow avalanche formation, Rev. Geophys., 41, 1016, https://doi.org/10.1029/2002RG000123, 2003.
Šmilauer, V., Angelidakis, V., Catalano, E., Caulk, R., Chareyre, B., Chèvremont, W., Dorofeenko, S., Duriez, J., Dyck, N., Elias, J., Er, B., Eulitz, A., Gladky, A., Guo, N., Jakob, C., Kneib, F., Kozicki, J., Marzougui, D., Maurin, R., Modenese, C., Pekmezi, G., Scholtès, L., Sibille, L., Stransky, J., Sweijen, T., Thoeni, K., and Yuan, C.: Yade documentation, Zenodo [software], https://doi.org/10.5281/zenodo.5705394, 2021.
Thorsteinsson, T.: An analytical approach to deformation of anisotropic ice-crystal aggregates, J. Glaciol., 47, 507–516, https://doi.org/10.3189/172756501781832124, 2001.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Wautier, A., Geindreau, C., and Flin, F.: Linking snow microstructure to its macroscopic elastic stiffness tensor: A numerical homogenization method and its application to 3-D images from X-ray tomography, Geophys. Res. Lett., 42, 8031–8041, https://doi.org/10.1002/2015GL065227, 2015.
Yu, H. S. and Carter, J.: Rigorous similarity solutions for cavity expansion in cohesive-frictional soils, Int. J. Geomech., 2, 233–258, https://doi.org/10.1061/(ASCE)1532-3641(2002)2:2(233), 2002.
Zhao, T.: Coupled DEM-CFD Analyses of Landslide-Induced Debris Flows, Springer, https://doi.org/10.1007/978-981-10-4627-8, 2017.
Short summary
This paper presents the evaluation of a numerical discrete element method (DEM) by simulating cone penetration tests in different snow samples. The DEM model demonstrated a good ability to reproduce the measured mechanical behaviour of the snow, namely the force evolution on the cone and the grain displacement field. Systematic sensitivity tests showed that the mechanical response depends not only on the microstructure of the sample but also on the mechanical parameters of grain contacts.
This paper presents the evaluation of a numerical discrete element method (DEM) by simulating...
