A medial axis based method for irregular grain shape representation in DEM simulations

Mede, Tijan; Chambon, Guillaume; Hagenmuller, Pascal; Nicot, François

doi:10.1007/s10035-017-0785-7

Cited by 21 publications

(15 citation statements)

References 30 publications

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“…The ice structure itself is then segmented into individual grains by detecting potential weak points based on local geometrical criteria (Hagenmuller et al, ). For the sake of computational efficiency, the actual shape of every grain in DEM simulations is modeled by packing the volume of the grain with a set of overlapping spherical discrete elements (Mede et al, ). There is a trade‐off between the grain approximation accuracy (and consequently the mechanical simulation accuracy) and the number of utilized spherical discrete elements (and consequently the numerical cost of the simulation).…”

Section: Methodsmentioning

confidence: 99%

“…There is a trade‐off between the grain approximation accuracy (and consequently the mechanical simulation accuracy) and the number of utilized spherical discrete elements (and consequently the numerical cost of the simulation). The optimal level of approximation was determined by a comprehensive sensitivity analysis of the macroscopic simulated response of a snow sample to compressive (Mede et al, ) as well as shear loading. These approximated grains are spatially arranged according to the initial microstructure.…”

Section: Methodsmentioning

confidence: 99%

“…Lastly, the mass of each grain was derived from the original binary image. Due to volumetric errors induced by grain approximation (Mede et al, ), this results in an effective density typically increased by 15% compared to that of ice.…”

Section: Methodsmentioning

confidence: 99%

“…The present study exploits an original numerical approach, based on the discrete element method (DEM; Cundall & Strack, 1979), which has been developed in order to simulate the mechanical response of snow samples to external loading (Hagenmuller et al, 2015;Mede et al, 2018). The model takes X-ray microtomography images of snow as input information.…”

Section: Methodsmentioning

confidence: 99%

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Snow Failure Modes Under Mixed Loading

Mede

Chambon

Hagenmuller

et al. 2018

Geophysical Research Letters

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The mechanical response of snow to mixed‐mode shear and normal loading is the key ingredient for snow avalanche modeling and strongly depends on microstructural characteristics. A discrete element numerical model was developed, which enables the simulation of large‐strain response of snow samples directly described by their full microstructure obtained through X‐ray microtomography. The model offers new insights into the failure mechanism as well as postfailure response of snow in mixed‐mode loading. Three distinct failure modes are identified, depending on the value of applied normal stress. Above a certain threshold normal stress, the failure is characterized by a structural collapse that decomposes the snow sample into a set of cohesionless grains. It is shown that the collapse is a dynamic process, which, once initiated, develops independently of shearing. This behavior was consistently observed for different snow types, including faceted crystals typically composing weak layers.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Snow Failure Modes Under Mixed Loading

Mede

Chambon

Hagenmuller

et al. 2018

Geophysical Research Letters

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“…This problem, namely the comparability of experiments and simulations, can be tackled in two ways. First, on the modeling side, the representation of microstructure in DEM could be made more sophisticated (Mede et al, 2018) to represent the true microstructure by only using spheres. Second, it is possible to explore the problem also from the experimental side, and experimentally create synthetic microstructures that closely resemble ideal sphere assemblies.…”

Section: Introductionmentioning

confidence: 99%

Ice Spheres as Model Snow: Tumbling, Sintering, and Mechanical Tests

et al. 2019

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The snow microstructure is crucial for the mechanical behavior of snow, but is usually simplified in numerical models. In Discrete Element Models (DEM), often used in snow mechanics, the microstructure is typically represented by sphere assemblies. This renders a model validation difficult, as the real snow crystal shapes affect the actual contacts and consequently the macromechanical behavior. To approach this problem from the experimental side, we created simplified microstructures comprising spherical ice particles and examined this model snow under structural and mechanical aspects. We developed a new method to create uniform ice spheres and performed a detailed particle characterization using 3D computed tomography (CT). We examined sintered sphere assemblies to relate microstructural and macromechanical properties in a geometrically well-defined system. Microstructural variation was created by varying the sample density and sintering time, to study the role of the number and size of contacts. 3D CT scans were taken of sintered sphere samples, which were then tested in unconfined compression experiments together with a nature identical snow type as a reference. The scans were evaluated regarding the number of particles and contacts, and were used to compute the elastic modulus, as additional mechanical property. The results of the particle characterization showed the spherical shape and sharp size-distribution of the particles, which are the main prerequisites for model validation. The CT image analysis showed the reproducibility of the sphere assemblies and can be applied for efficient reconstruction of the experimental samples as initial condition for simulations. The mechanical properties conform with the reference snow and the expectations from literature, however, the CT scans revealed a complex geometry of the sintered contacts with measurable impact on the mechanical properties.

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Exact and Optimal Conversion of a Hole-free 2d Digital Object into a Union of Balls in Polynomial Time

Sivignon

2022

Lecture Notes in Computer Science

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This paper addresses the problem of converting a 2d digital object, i.e. a set 𝑆 of points in ℤ 2 , into a finite union of balls ℬ centered on ℝ 2 , such that the digitization of ℬ is exactly 𝑆 and the cardinality of ℬ is minimum. We prove that, for the specific case of 2d hole-free digital objects, there exists a greedy polynomial-time algorithm. The algorithm is based on the same principle as the simple greedy optimal algorithm for the interval cover problem. After bringing to light under which conditions the latter algorithm can be extended to tree-like structures, we show that such a structure can be defined for any hole-free 2d digital object, so that the extended algorithm applies.

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A medial axis based method for irregular grain shape representation in DEM simulations

Cited by 21 publications

References 30 publications

Snow Failure Modes Under Mixed Loading

Snow Failure Modes Under Mixed Loading

Ice Spheres as Model Snow: Tumbling, Sintering, and Mechanical Tests

Exact and Optimal Conversion of a Hole-free 2d Digital Object into a Union of Balls in Polynomial Time

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