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Abstract/Summary
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<jats:p>Abstract. Snow is a complex porous material presenting a variety of microstructural patterns. This microstructure largely controls the mechanical properties of snow, although the relation between the micro and macro properties remains to be better understood. Recent developments based on the discrete element method (DEM) and three-dimensional microtomographic data make it possible to reproduce numerically the brittle mechanical behaviour of snow. However, these developments lack experimental evaluation so far. In this study, we evaluate a DEM numerical model by reproducing cone penetration tests on centimetric snow samples. The microstructures of different natural snow samples were captured with X-ray microtomography before and after the cone penetration test, from which the grain displacements induced by the cone could be inferred. The tests were conducted with a modified snow micropenetrometer (5 mm cone diameter), which recorded the force profile at a high resolution. In the numerical model, an elastic–brittle cohesive contact law between snow grains was used to represent the cohesive bonds. The initial positions of the grains and their contacts were directly derived from the tomographic images. The numerical model was evaluated by comparing the measured force profiles and the grain displacement fields. Overall, the model satisfactorily reproduced the force profiles in terms of mean macroscopic force (mean relative error of about 20 %) and the amplitude of force fluctuations (mean relative error of about 55 %), while the correlation length of force fluctuations was more difficult to reproduce (mean relative error of about 40 % for two samples out of four and by a factor ≥ 8 for the other two). These characteristics were, as expected, highly dependent on the tested sample microstructure, but they were also sensitive to the choice of the micromechanical parameters describing the contact law. A scaling law was proposed between the mechanical parameters, the initial microstructure characteristics and the mean macroscopic force obtained with the DEM numerical model. The model could also reproduce the measured deformation around the cone tip (mean grain displacement relative error of 57 % along the horizontal axis), with a smaller sensitivity to the contact law parameterisation in this case. These detailed comparisons between numerical and experimental results give confidence to the reliability of the numerical modelling strategy and opens promising prospects to improve the understanding of snow mechanical behaviour.
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Hinweis
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DeepGreen-ID: 086651457dcc4916881ecd7bf0a8fa44 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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