EGU2020-10203, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-10203
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Microstructure-based modeling of snow using the material point method and finite strain elastoplasticity

Lars Blatny1, Henning Löwe2, Stephanie Wang3, Chenfanfu Jiang4, and Johan Gaume1,2
Lars Blatny et al.
  • 1Snow and Avalanche Simulation Laboratory (SLAB), Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
  • 2WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
  • 3Department of Mathematics, University of California, Los Angeles, USA
  • 4Computer and Information Science Department, University of Pennsylvania, Philadelphia, USA

The mechanical response of snow depends on its microstructural geometry. Parameters such as porosity and orientation (degree of anisotropy) are examples of microstructural parameters that can affect snow mechanical properties. Numerical simulations of snow microstructure obtained from X-ray computer tomography have aided researchers in investigating the elastic response and strength of snow. However, we lack insight into the post-peak and plastic response of snow, which in most previous studies have been oversimplified assuming (quasi-)brittle behavior. We propose studying both the elastic and post-peak behavior using the material point method (MPM), a hybrid Eulerian-Lagrangian continuum numerical method. A major advantage of MPM compared to the (classical) finite element method (FEM) is its ability to handle large deformation processes. Moreover, as a continuum method, it is significantly less computational expensive than the discrete element method (DEM). We independently study the influence of the microstructural parameters on macroscopic quantities, such as elastic modulus, strength, energy release rate and plasticity index, in mixed-mode shear-compression loading simulations. This is accomplished by using the leveled gaussian random field (GRF) approach to generate snow samples with desired microstructural properties. The ice matrix of the microstructure is modeled in the elastoplastic framework with a strain-softening Drucker-Prager failure criterion. Based on the relationships discovered through these numerical experiments, we aim to develop a microstructure-based homogenized constitutive snow model. This study will contribute to improve large-scale snow mechanical models with applications in the simulation of e.g. snow slab avalanche release, avalanche dynamics and snow-tire interaction.

How to cite: Blatny, L., Löwe, H., Wang, S., Jiang, C., and Gaume, J.: Microstructure-based modeling of snow using the material point method and finite strain elastoplasticity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10203, https://doi.org/10.5194/egusphere-egu2020-10203, 2020

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