Microstructural Origin of Propagating Compaction Patterns in Porous Media

Blatny, Lars; Berclaz, Paul; Guillard, François; Einav, Itai; Gaume, Johan

doi:10.1103/physrevlett.128.228002

Cited by 8 publications

(3 citation statements)

References 25 publications

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“…MPM is a Eulerian-Lagrangian particle-based method initially developed by Sulsky et al (1994). Due to its ability to handle processes including large deformations, fractures and collisions, this elegant hybrid method found great interest over the last two decades, both in geomechanics, e.g., for the modeling of fluid-structure interaction (York II et al, 2000), porous media micromechanics (Blatny et al, 2021(Blatny et al, , 2022, granular flows (Dunatunga & Kamrin, 2015), snow avalanche release (Gaume et al, 2019;Trottet et al, 2022), snow avalanche dynamics (Li et al, 2021), glacier calving (Wolper et al, 2021), debris flows (Vicari et al, 2022), landslides (Soga et al, 2016 and rockslides (Cicoira et al, 2022), as well as in computer graphics (Stomakhin et al, 2013;Jiang et al, 2016;Schreck & Wojtan, 2020;Daviet & Bertails-Descoubes, 2016). After its first application to snow slab avalanches, Gaume et al (2019) analysed crack propagation and slab fracture patterns and reported crack speeds above 100 m/s on steep terrain.…”

Section: Introductionmentioning

confidence: 99%

A Depth-Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

Guillet¹,

Blatny²,

Trottet³

et al. 2023

Preprint

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Shallow landslides pose a significant threat to people and infrastructure. While often modeled based on limit equilibrium analysis, finite or discrete elements, continuum particle-based approaches like the Material Point Method (MPM) have more recently been successful in modeling their full 3D elasto-plastic behavior. In this paper, we develop a depth-averaged Material Point Method (DAMPM) to efficiently simulate shallow landslides over complex topography based on both material properties and terrain characteristics. DAMPM is an adaptation of MPM with classical shallow water assumptions, thus enabling large-deformation elasto-plastic modeling of landslides in a computationally efficient manner. The model is here demonstrated on the release of snow slab avalanches, a specific type of shallow landslides which release due to crack propagation within a weak layer buried below a cohesive slab. Here, the weak layer is considered as an external shear force acting at the base of an elastic-brittle slab. We validate our model against previous analytical calculations and numerical simulations of the classical snow fracture experiment known as Propagation Saw Test (PST). Furthermore, large scale simulations are conducted to evaluate the shape and size of avalanche release zones over different topographies. Given the low computational cost compared to 3D MPM, we expect our work to have important operational applications in hazard assessment, in particular for the evaluation of release areas, a crucial input for geophysical mass flow models. Our approach can be easily adapted to simulate both the initiation and dynamics of various shallow landslides, debris and lava flows, glacier creep and calving.

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Section: Introductionmentioning

confidence: 99%

A Depth-Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

Guillet¹,

Blatny²,

Trottet³

et al. 2023

Preprint

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show abstract

“…[6] The largest classes of nonlinear elastic materials are porous media, whose mechanical response can be tailored through intrinsic material properties and pore architecture. [7][8][9][10] Engineering foams have been extensively studied to understand the physical phenomena that govern density, stiffness, and strength. [9,11] In particular, quasi-zero stiffness (QZS) [5] materials are nonlinear materials that are closely related to foams, which have a stress-strain behavior that includes a plateau stress region; this behavior enables energy absorption and vibration isolation.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Design of Zero‐Stiffness Elastomer Springs Using Machine Learning

Kim

Tawfick

King

2022

Advanced Intelligent Systems

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Architected metamaterials exhibit complex stress–strain responses, such as quasi‐zero stiffness (QZS) plateau response useful in vibration and energy absorption, by exploiting elastic instabilities such as buckling. However, the design of metamaterials with prescribed nonlinear mechanical properties is challenging due to the difficulty in accurately predicting nonlinear mechanical responses such as buckling and self‐contact, as well as geometric and material uncertainties. Herein, additive manufacturing (AM) with machine learning (ML) to demonstrate data‐driven modeling and the design of nonlinear elastomeric springs with a broad stress plateau is combined. 243 elastomer chi (χ) spring parts with different design parameters fabricated by AM are tested. A Gaussian process (GP) model is trained on key features of the measured mechanical response and predicts the mechanical response within a 3% error with as few as 97 parts. To account for the geometric and material uncertainties, the GP model to develop an uncertainty‐aware design optimization approach to tailor the mechanical response based on the covariance matrix adaptation evolution strategy (CMA‐ES) is utilized. Excellent agreement is demonstrated between the designed response and measured response over the range of plateau stress considered. The research illustrates the promise of experimental data‐driven approaches and AM in enabling complex material design.

show abstract

“…MPM is a Eulerian-Lagrangian particle-based method initially developed by Sulsky et al (1994). Due to its ability to handle processes including large deformations, fractures and collisions, this elegant hybrid method found great interest over the last two decades, both in geomechanics, for example, for the modeling of fluid-structure interaction (York II et al, 2000), porous media micromechanics (Blatny et al, 2021(Blatny et al, , 2022, granular flows (Dunatunga & Kamrin, 2015), snow avalanche release (Gaume et al, 2019;Trottet et al, 2022), snow avalanche dynamics (Li et al, 2021), glacier calving (Wolper et al, 2021), debris flows (Vicari et al, 2022), landslides (Soga et al, 2016) and rockslides (Cicoira et al, 2022), as well as in computer graphics (Daviet & Bertails-Descoubes, 2016;Jiang et al, 2016;Schreck & Wojtan, 2020;Stomakhin et al, 2013).…”

mentioning

confidence: 99%

A Depth‐Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

et al. 2023

Self Cite

View full text Add to dashboard Cite

Shallow landslides pose a significant threat to people and infrastructure. Despite significant progress in the understanding of such phenomena, the evaluation of the size of the landslide release zone, a crucial input for risk assessment, still remains a challenge. While often modeled based on limit equilibrium analysis, finite or discrete elements, continuum particle‐based approaches like the Material Point Method (MPM) have more recently been successful in modeling their full 3D elasto‐plastic behavior. In this paper, we develop a depth‐averaged Material Point Method (DAMPM) to efficiently simulate shallow landslides over complex topography based on both material properties and terrain characteristics. DAMPM is a rigorous mechanical framework which is an adaptation of MPM with classical shallow water assumptions, thus enabling large‐deformation elasto‐plastic modeling of landslides in a computationally efficient manner. The model is here demonstrated on the release of snow slab avalanches, a specific type of shallow landslides which release due to crack propagation within a weak layer buried below a cohesive slab. Here, the weak layer is considered as an external shear force acting at the base of an elastic‐brittle slab. We verify our model against previous analytical calculations and numerical simulations of the classical snow fracture experiment known as Propagation Saw Test (PST). Furthermore, large scale simulations are conducted to investigate cross‐slope crack propagation and the complex interplay between weak layer dynamic failure and slab fracture. In addition, these simulations allow us to evaluate and discuss the shape and size of avalanche release zones over different topographies. Given the low computational cost compared to 3D MPM, we expect our work to have important operational applications in hazard assessment, in particular for the evaluation of release areas, a crucial input for geophysical mass flow models. Our approach can be easily adapted to simulate both the initiation and dynamics of various shallow landslides, debris and lava flows, glacier creep and calving.

show abstract

Microstructural Origin of Propagating Compaction Patterns in Porous Media

Cited by 8 publications

References 25 publications

A Depth-Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

A Depth-Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

Modeling and Design of Zero‐Stiffness Elastomer Springs Using Machine Learning

A Depth‐Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

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