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The Discrete Element Method (DEM) has been successfully used to further understand GM behaviour where experimental means are not possible or limited. However, the vast majority of DEM publications use simplified spheres with rolling friction to account for particle shape, with a few using clumped spheres and super quadratics to better capture grain geometric detail. In this study, we compare the shear strength of packed polyhedral assemblies to spheres with rolling resistance to account for shape. Spheres were found to have the highest shear resistance as the limited rolling friction model could not capture the geometric of rotation grains which caused reordering and dilation. This geometric arrangement causes polyhedra to align faces in the shear direction, reducing the resistance to motion. Conversely, geometric interlocking can cause jamming resulting in a dramatic increase in shear resistance. Particle aspect ratio (elongation and fatness) was found to significantly
lower shear resistance, while more uniform aspect ratio’s increased shear resistance with shape non-convexity showing extremes of massive slip or jamming. Thus, while spheres with rolling friction may yield bulk shear strength similar to some polyhedra with a mild aspect ratio, the grain scale effect that leads to compaction and jamming from rotation and interlocking is missed. These results shed light on the complex impact that individual grain shape has on bulk behaviour and its importance.

Powders &amp; Grains 2021

A study on the effect of grain morphology on shear strength in granular materials

[EPJ Web of Conferences, Volume 249 (2021)](https://www.epj-conferences.org/articles/epjconf/abs/2021/03/contents/contents.html)

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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.

poster

We use three-dimensional particle dynamics simulations to investigate the microstructure evolution of granular material subjected to isochoric cyclic shearing, driving the system to a liquefaction state. The cyclically sheared assembly presents a realistic macroscopic response as observed in physical experiments. By analyzing the contact network evolution in the post-liquefaction period, we show that the onset of liquefaction state is characterized by a sudden drop of coordination number and a fragile particle connectivity network. The simulation suggests a critical coordination number for exiting the liquefaction state. Evolution of fabric anisotropy combined with coordination number implies the isotropic and anisotropic gain or loss of contacts at certain durations of a post-liquefaction loading cycle.

Geometrical network of granular materials under isochoric cyclic shearing

3D printing is emerging as one of the most promising methods to manufacture Pharmaceutical dosage forms as it offers multiple advantages such as personalization of dosage forms, polypill, fabrication of complex dosage forms etc. 3D printing came into existence in 1980s but its use was extended recently to pharmaceutical industry along with the approval of first 3D printed tablet Spritam by FDA in 2015. Spritam was manufactured by Aprecia pharmaceuticals using binder jetting technology. Binder jet 3D printing involves a hopper for powder discharge and printheads for ink jetting. The properties of tablets are highly dependent upon the discharge quality of powder mixture from the hopper and jetting of the ink/binder solution from the printhead nozzle. In this study, numerical models were developed using Discrete element method (DEM) to gain better understanding of the binder jet 3D printing process. The DEM modeling of hopper discharge was performed using in-house DEM code to study the effect of raw material attributes such as powder bed packing density (i.e. particle size, particle density etc.) on the printing process, especially during powder bed preparation. This DEM model was further validated experimentally, and the model demonstrated good agreement with experimental results.

DEM based investigation of powder packing in 3D printing of pharmaceutical tablets

We are numerically and experimentally studying the response of a 3d granular system to cyclic perturbations to investigate reversibility and memory effects. We are especially interested in translations and rotations of particles are affected by the inter-particle friction coefficient. We find that at low friction, the rotations are homogeneously distributed in the system; the motion of particles is mostly reversible and the system exhibit a very strong memory response. In contrast, at high friction, the rotations are located in a narrow shear band, and are mostly irreversible which leads to a much less pronounced memory response of the system. This can be explained by the need for the system to overcome a large sliding force limit which is only possible for a small proportion of particles, leading to a non-reversible motion.

Effects of interparticle friction on the response of 3D cyclically compressed granular material

This paper presents a Computational Fluid Dynamics (CFD) model on the effect of capillary pressure on the retention behaviour of a granular material. The model proposes an unprecedented CFD insight into the onset of liquid menisci at the inter-particles contact under varying hydraulic conditions. The present work models the material grains as smooth spherical particles that define a porous network filled by two interstitial fluids: air and silicon oil. The numerical model has been subsequently validated against experimental measurements of the degree of saturation at different capillary pressures taken by Dullien et al. [F.A. Dullien, C. Zarcone, I.F. MacDonald, A. Collins, R.D. Bochard. J. Colloid Interface Sci. 127, 2 (1989)] in a system of smooth glass beads flooded with silicon oil. Results from the numerical simulations confirm the good capability of the model to reproduce the experimental retention behaviour of the granular material. Finally, the present paper laid the basis for future CFD studies on the effect of various factors (e.g. hydraulic hysteresis, surface roughness and/or grain shape) on the capillary pressure acting at the inter-particle contact.

CFD modelling of the effect of capillary pressure on retention behaviour of water menisci at inter-particle contacts

The erosion of a cohesive soil by an impinging turbulent jet is observed, for instance, during the landing of a spacecraft or involved in the so-called jet erosion test. To provide a quantitative understanding of this situation for cohesive soils, we perform experiments using a model cohesion controlled granular material that allows us to finely tune the cohesion between particles while keeping the other properties constant. We investigate the response of this cohesive granular bed when subjected to an impinging normal turbulent jet. We characterize experimentally the effects of the cohesion on the erosion threshold and the development of the crater. We demonstrate that the results can be rationalized by introducing a cohesive Shields number that accounts for the inter-particles cohesion force. The results of our experiments highlight the crucial role of cohesion in erosion processes.

Erosion of a cohesive granular material by an impinging turbulent jet

Root growth alters soil fabric and consequently its mechanical and physical properties. Recent studies show that roots induce compaction of soil in their immediate vicinity, a region that is central for plant health. However, high-quality quantification of root influence on the soil fabric, able to inform computational models is lacking from the literature. This study quantifies the relationship between soil physical characteristics and root growth, giving special emphasis on how roots in early-stage formation influence the physical architecture of the surrounding soil structure. High-resolution X-ray micro-Computed Tomography (µCT) is used to acquire three-dimensional images of two homogeneously-packed samples. It is observed that the void ratio profile extending from the soil-root interface into the bulk soil is altered by root growth. The roots considerably modify the immediate soil physical characteristics by creating micro-cracks at the soil-root interface and by increasing the void ratio. This paper presents the mechanisms that led to the observed structure as well as some of the implications that it has in such a dynamic zone.


Imaging the root–rhizosphere interface using micro computed tomography: quantifying void ratio and root volume ratio profiles

The Standard Penetration Test (SPT) is the most widely used method for dynamic testing of soils. The test is simple and robust but difficult to control and not fully standardized. As a result, experimental results typically show large variations and poor repeatability. To mitigate that correction factors such as energy normalization and rod length have been introduced in SPT practice. This study provides an examination of the two correction factors using models based on the discrete element method (DEM).

DEM examination of SPT correction factors

The surfaces of many planetary bodies, including asteroids, moons, and planets, are composed of rubble-like grains held together by varying levels of gravitational attraction and cohesive forces. Future instrumentation for operation on, and interacting with, such surfaces will require efficient and effective design principles and methods of testing. Here we present results from the EMPANADA experiment (Ejecta-Minimizing Protocols for Applications Needing Anchoring or Digging on Asteroids) which flew on several reduced gravity parabolic flights. EMPANADA studies the effects of the insertion of a flexible probe into a granular medium as a function of ambient gravity. This is done for an idealized 2D system as well as a more realistic 3D sample. To quantify the dynamics inside the 2D granular material we employ photoelasticity to identify the grain-scale forces throughout the system, while in 3D experiments we use simulated regolith. Experiments were conducted at three different levels of gravity: martian, lunar, and microgravity. In this work, we demonstrate that the photoelastic technique provides results that complement traditional load cell measurements in the 2D sample, and show that the idealized system exhibits similar behaviour to the more realistic 3D sample. We note that the presence of discrete, stick-slip failure events depends on the gravitational acceleration.

Probing regolith-covered surfaces in low gravity

In industrial powder processing, precise control of environmental temperature is difficult especially for large production facilities. A better knowledge of powder behavior modification due to temperature variation will help to improve product quality and consistency. From a fundamental point of view, the effect of temperature on powder flow and packing dynamics is still poorly understood. In particular, because temperature modifies the complex interplay between the different forces acting at the contact between the grains. The packing dynamics of a set of different powders (lactose, cacao and dried milk powder) has been investigated with a tapping experiment. After the filling procedure, the sample is heated and the evolution of the density is measured after each tap. We show that the packing dynamics is drastically influenced even for low temperature changes. Slight increase of temperature affects both the packing kinematics and the packing range characterised by the classical Hausner ratio analysis. Finally, the different physical mechanisms that could explain these modifications are discussed. The results of this preliminary study demonstrate the importance of temperature in powder behaviour and strongly motivate further investigations.


Packing dynamics of powders at high temperature

Industrial-scale discrete element simulations typically generate Gigabytes of data per time step, which implies that even opening a single file may require 5 - 15 minutes on conventional magnetic storage devices. Data science’s inherent multi-disciplinary nature makes the extraction of useful information challenging, often leading to undiscovered details or new insights. This study explores the potential of statistical learning to identify potential regions of interest for large scale discrete element simulations. We demonstrate that our in-house knowledge discovery and data mining system (KDS) can decompose large datasets into i) regions of potential interest to the analyst, ii) multiple decompositions that highlight different aspects of the data, iii) simplify interpretation of DEM generated data by focusing attention on the interpretation of automatically decomposed regions, and iv) streamline the analysis of raw DEM data by letting the analyst control the number of decomposition and the way the decompositions are performed. Multiple decompositions can be automated in parallel and compressed, enabling agile engagement with the analyst’s processed data. This study focuses on spatial and not temporal inferences.

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Geometrical network of granular materials under isochoric cyclic shearing

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