United States

Poroelasticity theory predicts wave velocities in a saturated porous medium through a coupling between the bulk deformation of the solid skeleton and porous fluid flow. The challenge emerges below the characteristic wavelengths at which hydrodynamic interactions between grains and pore fluid become important. We investigate the pressure and volume fraction dependence of compressional- and shear-wave velocities in fluid-saturated, random, isotropic, frictional granular packings. The lattice Boltzmann method (LBM) and discrete element method (DEM) are two-way coupled to capture the particle-pore fluid interactions; an acoustic source is implemented to insert a traveling wave from the fluid reservoir to the saturated medium. We extract wave velocities from the acoustic branches in the wavenumber-frequency space, for a range of confining pressures and volume fractions. For random isotropic granular media, the pressure-wave velocity data collapse on a single curve when scaled properly by the volume fraction.

Powders &amp; Grains 2021

Direct numerical simulation of wave propagation in saturated random granular packings using coupled LBM-DEM

[EPJ Web of Conferences, Volume 249 (2021)](https://www.epj-conferences.org/articles/epjconf/abs/2021/03/contents/contents.html)

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Welcome to the 2021 Powders and Grains conference. Please review the event's **Code of Conduct** [here](https://drive.google.com/file/d/1P_bOrjI2jSE55twRPVzWl5VkfARR-qBL/view?usp=sharing). 


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Powders & Grains 2021

Powders & Grains 2021 will be held in Buenos Aires (Argentina, VIRTUAL) July 5, 13, 21, 29 and Aug 6, 2021. The aim of the conference is to give an up-to-date picture of the broad research field of granular media, powders and grains. Contributions from experts around the world will focus on research topics that cover a wide range of open problems in the field.

technical paper

Discrete element modelling (DEM) is widely used to simulate granular systems, nowadays routinely on graphical processing units. Graphics processing units (GPUs) are inherently designed for parallel computation, and recent advances in the architecture, compiler design and language development are allowing general-purpose computation to be computed on multiple GPUs. Application of DEM to bonded particle systems are much less common, with a number of open research questions remaining. This study outlines a Bonded-Particle Research DEM Framework, PyBONDEM-GPU, written in Python. This framework leverages the parallel nature of GPUs for computational speed-up and the rapid prototype flexibility of Python. Python is faster and easier to learn than classical compiled languages, making computational simulation development accessible to undergraduate and graduate engineers. PyBONDEM-GPU leverages the Numba-CUDA module to compile Python syntax for execution on GPUs. The framework enables research of fibre pull-out from fibre-matrix embeddings. Bonds are simulated between all interacting particles. The performance of PyBONDEM-GPU is compared against Python CPU implementations of PyBONDEM using the Numpy and Numba-CPU Python modules. PyBONDEM-GPU was found to be 1000 times faster than the Numpy implementation and 4 times faster than the Numba-CPU implementation to resolve forces and to integrate the equations of motion.

PyBONDEM-GPU: a discrete element bonded particle Python research framework – Development and examples

Copper mining produces significant amounts of associate waste, leading to the construction of huge mining waste dumps in the highly seismic zone of the Andes Mountains. To analyze the seismic stability of these deposits, it is necessary to characterize the mechanical properties of these materials in laboratory, which is quite difficult due to the large size of particles composing these structures. In this study, the global stability of mine waste dumps is analyzed by means of discrete element simulations. Three analogues upscaled particle size distributions were generated from the original PSD. The particles composing the dump were modeled using regular polygons. The modeled dumps were subject to a seismic loading by applying a velocity signal on the boundary walls, which was integrated directly from accelerometers database. The results show that failure in these structures is produced by infinite slope, for samples scaled by a factor until ten. This methodology is encouraging for the analysis of the global stability of mine waste dumps and for forecasting the runout distance after failure.

Discrete modeling of waste rock dumps stability under seismic loading

To understand the typically heterogeneous flowing behavior of granular materials, it is important to combine flow tests with three-dimensional imaging. To probe the flow behavior of granular materials over a wide range of flow rates, it is imperative to be able to impose such flow rates in a well controlled manner while performing imaging tests that are compatible with all imposed flow rates. Achieving both flow control and bulk imaging capacity is challenging for a number of reasons. Here, we describe the design of a setup in which we are able to do imaging while imposing a constant overall shear rate on a granular material. We characterize the setup in which flow tests will be performed, which consists of a bottom-driven cone-plate or double-cone design. We show that the setup can be integrated in x-ray microtomography devices to aid particle tracking based flow measurements. The design is also compatible with typical rheometer setups. We also perform high
speed imaging of a granular flow in an ultra-fast x-ray scanner, for which we provide proof-of-principle data in a simplified shear setup. The designed flow geometry is also compatible with said high speed imaging facility, where particle image velocimetry can be employed to extract quantitative flow field data.

Improved evaluation of granular media flows using an X-ray scanning compatible cone-plate setup

The numerical modelling of geotechnical problems often poses major challenges when large displacements and strain localization are involved. Conventional continuum mechanical approaches like the finite element method (FEM) or the finite difference method (FDM) suffer from mesh distortion and numerical inaccuracy when large deformations are involved. In addition, they require the use of appropriate constitutive models to simulate the soil behaviour. The distinct element method is a promising alternative for large deformation analyses. It does not have the limitations resulting from the numerical discretization of the continuum- and not need a constitutive model since the macroscopic response results from the individual particle interaction. However, the maximum number of particles and therefore the domain of the simulation is nowadays limited by the available computational capacity. To overcome this limitation, a coupled DEM-FDM approach is proposed used to optimize the number of particles for a combined numerical domain consisting of areas of large and small displacements. The performance of the coupled DEM-FDM approach is investigated by simulating cone penetration tests in coarse grained soils.

Coupled DEM-FDM simulation of cone penetration tests in coarse grained soils

Some years ago, Harth et al. experimentally explored the steady state dynamics of a heated granular gas of rod-like particles in microgravity [K. Harth et al. Phys. Rev. Lett. 110, 144102 (2013)]. Here, we report numerical results that quantitatively reproduce their experimental findings and provide additional insight into the process. A system of sphero-cylinders is heated by the vibration of three flat side walls, resulting in one symmetrically heated direction, one non-symmetrically heated direction, and one non-heated direction. In the non-heated direction, the speed distribution follows a stretched exponential distribution p(v) ∝ exp(−(|v|/C)^1.5 ).
In the symmetrically heated direction, the velocity statistics at low speeds is similar but it develops pronounced exponential tails at high speeds. In the non-symmetrically heated direction (not accessed experimentally), the distribution also follows p(v) ∝ exp(−(|v|/C)^1.5 ), but the velocity statistics of rods moving toward the vibrating wall resembles the indirectly excited direction, whereas the velocity statistics of those moving away from the wall resembles the direct excited direction.

Continuously heated granular gas of elongated particles

Using a discrete-element approach and a bonding interaction law, we model and test crushable inherently anisotropic structures reminiscent of the layering found in sedimentary and metamorphic rocks. By systematically modifying the level of inherent anisotropy, we characterize the evolution of the failure strength of circular rock samples discretized using a modified Voronoi tesselation under diametral point loading at different orientations relative to the sample’s layers. We characterize the failure strength, which can dramatically increase as the loading becomes orthogonal to the rock layers. We also describe the evolution of the macroscopic failure modes as a function of the loading orientation and the energy consumption at fissuring. Our simulation strategy lets us conclude that the length of bonds between Voronoi cells controls the energy being consumed in fissuring the rock sample, although failure modes and strength are considerably changing. We end up this work showing that the microstructure is largely affected by the level of inherent anisotropy and loading orientation.

Strength and energy consumption of inherently anisotropic rocks at failure

Tsunami-like waves can arise from large-scale geological events such as the collapse of a mountain flank or a volcano into a lake or an ocean. We here mimic this situation at the laboratory scale. The landslide is modeled by the sudden release of a rectangular granular column, which impacts a still water layer and generates a wave. Through experiments varying both the column dimensions and the initial water depth, three regimes of nonlinear waves of different shapes are reported. The amplitude and width of the generated waves are governed by a local Froude number based on the velocity of the granular front at the water surface.

On water waves generated by gravity driven granular collapse

One striking difference between aggregates of flexible frictional fibres and other granular materials like rigid spheres is the effective cohesion of their assembly. While glue or capillary bridges are needed to shape aggregates of spherical particles and build sandcastles, for fibres, no need for glue to build a nest. Here we study an assembly of mono disperse flexible fibres. We first use X-ray microtomography to characterise the geometry of the initial assembly, the number of contact points and mean curvatures of the fibres. Using forcedisplacement measurements, we characterise the macroscopic cohesive strength of the aggregate by varying the geometry of the fibres, the fibres mechanicals properties and the packing of the preparation. Finally, we relate the macroscopic mechanical behaviour of the assembly with the filament reorganisation at the microscopic scale.

Cohesion of bird nests

The use of the Discrete Element Method to model engineering structures implementing granular materials has proven to be an ecient method to response under various behaviour conditions. However, the computational cost of the simulations increases rapidly, as the number of particles and particle shape complexity increases. An aordable solution to render problems computationally tractable is to use graphical processing units (GPU) for computing. Modern GPUs oer up 10496 compute cores, which allows for a greater parallelisation relative to 32-cores oered by high-end Central Processing Unit (CPU) compute. This study outlines the application of BlazeDEM-GPU, using an RTX 2080Ti GPU (4352 cores), to investigate the influence of the modelling of particle shape on the lateral pull behaviour of granular ballast systems used in railway applications.
The idea is to validate the model and show the benefits of simulating non-spherical shapes in future large-scale tests. The algorithm, created to generate the shape of the ballast based on real grain scans, and using polyhedral shape approximations of varying degrees of complexity is shown. The particle size is modelled to scale. A preliminary investigation of the effect of the grain shape is conducted, where a sleeper lateral pull test is carried out in a spherical grains sample, and various polyhedral grains samples.
Results show that elementary polyhedral shape representations recreate some of the characteristic responses in the lateral pull test,
such as stick/slip phenomena and force chain distributions, which looks promising for future works on railway simulations.
These responses cannot be recreated with simple spherical grains, even when heuristics are added, which requires additional calibration and approximations.
The significant reduction in time when using non-spherical grains also implies that larger granular systems can be investigated.

Modelling realistic ballast shape to study the lateral pull behaviour using GPU computing

We develop a numerical tool for particle-based simulations of Aeolian sand transport. Our model combines a Discrete-Element-Method for the sand particles with an efficient hydrodynamic description of the average turbulent horizontal wind velocity field over the granular bed, which has been developed in previous work and accounts for the two-way coupling of the granular and fluid phases. However, here we implement our model within the open-source library LAMMPS for granular massively parallel simulations and incorporate a new grid coarsening scheme for the wind model. We show that our model quantitatively reproduces observed values of the steady-state (saturated) sand flux under various flow conditions. Furthermore, we model different conditions of mobile sand availability and find a strong dependence of the sand flux on this availability

Direct numerical simulation of wave propagation in saturated random granular packings using coupled LBM-DEM

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PyBONDEM-GPU: a discrete element bonded particle Python research framework – Development and examples

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Direct numerical simulation of wave propagation in saturated random granular packings using coupled LBM-DEM

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Next from Powders & Grains 2021

PyBONDEM-GPU: a discrete element bonded particle Python research framework – Development and examples

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Discrete element simulations of load transfer mechanisms for a reinforced granular embankment submitted to loading cycles

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