Quantifying Interparticle Forces and Heterogeneity in 3D Granular Materials

Hurley, Ryan; Hall, Stephen A.; Andrade, José E.; Wright, Jonathan P.

doi:10.1103/physrevlett.117.098005

Cited by 125 publications

(98 citation statements)

References 19 publications

(41 reference statements)

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“…The skeletal, nonhydrostatic distribution of force on a scale larger than the particle size was firmly established by experiments with optically sensitive discs Dantu, 1957;de Jong and Verruijt, 1969], 3-D X-ray diffraction [Hurley et al, 2016], and later DEM numerical experiments [Cundall and Strack, 1983].…”

Section: Force Chainsmentioning

confidence: 94%

“…The skeletal, nonhydrostatic distribution of force on a scale larger than the particle size was firmly established by experiments with optically sensitive discs [ Behringer et al ., ; Dantu , ; de Jong and Verruijt , ], 3‐D X‐ray diffraction [ Hurley et al ., ], and later DEM numerical experiments [ Cundall and Strack , ]. These observations were rationalized with the notion of “force chains” [ Antony , ] as illustrated in Figure .…”

Section: Kinematics Of Hydrogranular Mediamentioning

confidence: 99%

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On the kinematics and dynamics of crystal‐rich systems

2017

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Partially molten rocks, often called a mush, are examples of a hydrogranular mixture where the dynamics are controlled by both fluid and crystal‐crystal interactions. An obstacle to progress in understanding high‐temperature hydrogranular systems has been the lack of adequate levels of description of microphysical processes. Here we rationalize the hydrogranular kinematic and dynamic states by applying the concept of particle (crystal) force chains. We exemplify this with discrete‐element computational fluid dynamic simulations of the intrusion of a basaltic melt into an olivine‐basalt mush, where crystal‐scale force chains, crystal transport, and melt mixing are resolved. To describe the microscale kinematics of the system, we introduce the coordination number and the fabric tensors of particle contacts and forces. We quantify the changing contact and force fabric anisotropy, coaxiality, and the connectedness of the mush, under dynamic conditions. To describe the dynamics, particle and fluid characteristic response times are derived. These are used to define local and bulk Stokes numbers, and viscous and inertia numbers, which quantify the multiphase coupling under crystal‐rich conditions. We employ the Sommerfeld number, which describes the importance of crystal‐melt lubrication, with a viscous number to illustrate the dynamic regimes of crystal‐rich magmas. We show that the notion of mechanical “lock up” is not uniquely identified with a particular crystal volume fraction and that distinct mechanical behaviors can emerge simultaneously within a crystal‐rich system. We also posit that this framework describes magmatic fabrics and processes which “unlock” a crystal mush prior to eruption or mixing.

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Section: Force Chainsmentioning

confidence: 94%

Section: Kinematics Of Hydrogranular Mediamentioning

confidence: 99%

On the kinematics and dynamics of crystal‐rich systems

2017

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“…Finally, at the particle level, the model predicts particle rotations that on average compare well with those obtained in the experiment. Well beyond reproduction, the avatar paradigm affords the ability to see the evolution of interparticle forces, which are currently impossible to obtain from regular experiments, and which are an active area of research for single-crystal spherical particles [24]. Two modeling advancements afford the avatar paradigm higher fidelity: shape and more accurate boundary conditions.…”

Section: A C C E P T E D Mmentioning

confidence: 99%

All you need is shape: Predicting shear banding in sand with LS-DEM

Kawamoto

Andò

Viggiani

et al. 2018

Journal of the Mechanics and Physics of Solids

272

111

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This paper presents discrete element method (DEM) simulations with experimental comparisons at multiple length scales-underscoring the crucial role of particle shape. The simulations build on technological advances in the DEM furnished by level sets (LS-DEM), which enable the mathematical representation of the surface of arbitrarily-shaped particles such as sands. We show that this ability to model shape enables unprecedented capture of the mechanics of granular materials across scales ranging from macroscopic behavior to local behavior to particle behavior. Specifically, the model is able to predict the onset and evolution of shear banding in sands, replicating the most advanced high-fidelity experiments in triaxial compression equipped with sequential X-ray tomography imaging. We present comparisons of the model and experiment at an unprecedented level of quantitative agreement-building a one-to-one model where every particle in the more than 53,000-particle array has its own avatar or numerical twin. Furthermore, the boundary conditions of the experiment are faithfully captured by modeling the membrane effect, as well as the platen displacement and tilting. The results show a computational tool that can give insight into the physics and mechanics of granular materials undergoing shear deformation and failure, with computational times comparable to those of the experiment. One quantitative measure that is extracted from the LS-DEM simulations that is currently not available experimentally is the evolution of three dimensional force chains inside and outside of the shear band. We show that the rotations on the force chains are correlated to the rotations in stress principal directions.

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“…80 In addition, several other techniques not covered by the Focus Issue deserve mention since they provide contact force measurements for hard, frictional particles for which deformations are not directly observable. Using a combination of x-diffraction and X-ray tomography, Hurley et al 81 have successfully measured inter-particle forces for a small sample of non-transparent particles under compression, and at the singleparticle level. Chen et al 82 have shown that it is possible to use two-photon excitation to make pressure measurements within single ruby particles, based on shifts in the fluorescence spectrum.…”

Section: Measuring Inter-particle Forcesmentioning

confidence: 99%