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

Abstract

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.

Exploring the micromechanics of non-active clays by way of virtual DEM experiments

“…For the case of granular materials, microscale processes have been investigated experimentally in terms of the interparticle forces (Cavarretta, et al, 2010) and particle kinematics (Andò, et al, 2012a;Andò, et al, 2012b). The microscopic mechanisms observed experimentally have been translated into DEM (Discrete Element Method) models, which have been used as a virtual laboratory to investigate fundamental aspects of the macroscopic behaviour of soil (O' Sullivan, et al, 2006), including strain localisation (Kawamoto, et al, 2018;Iwashita & Oda, 1997), induced anisotropy (Guo & Zhao, 2012), soil crushing and aggregate deformability (Thornton, et al, 1996;Cheng, et al, 2003;Bolton, et al, 2008;Ueda et al, 2013;Asadi et al, 2018), wave propagation and small strain stiffness (Magnanimo et al, 2008;Mouraille, 2009;O'Donovan et al, 2012).…”

A geometry-based algorithm for cloning real grains 2.0

“…The ultimate goal of this study is to generate new "cloned" grains, that accurately capture and reproduced the morphological features of any given sample of real granular materials, with the aim of using them as part of DEM based engineering-scale simulations overcoming sample size constrains inherent to 3DXRCT scanning processes. This, together with recent works [21] that have shown the importance of shape when not only qualitatively, but quantitatively matching the mechanical behavior of real granular materials, promise to become a powerful tool to simulate engineering scale processes involving granular materials.…”

“…X-ray Computed Tomography scanning (3DXRCT) has made possible to recover real shapes of granular materials [26,27] such as Hostun sand [21] with very high detail and include them into DEM simulations [15,20]. However, costly equipment and specialized personal is needed to perform this 3D X-ray CT scans.…”

Multiscale modeling of large deformation in geomechanics

“…Further studies are needed to find more efficient solutions schemes, ie, adaptive multiscale homogenization, to mitigate the computational cost of the multiscale modeling. It is also desired to enrich the functionalities of current multiscale approach by considering grain morphology, particle breakage, or hydro‐mechanical coupling . Although all cases discussed in this paper have been based on 2D simulations, it is straightforward to further implement the code in 3D as the multiscale framework is proposed in generalized form and, both the adopted MPM solver ( NairnMPM ) and DEM solver ( YADE ) have built‐in 3D capabilities.…”