Three‐dimensional ellipsoidal discrete element modeling of granular materials and its coupling with finite element facets

Abstract

Purpose -The purpose of this paper is to develop a discrete element (DE) and multiscale modeling methodology to represent granular media at their particle scale as they interface solid deformable bodies, such as soil-tool, tire, penetrometer, pile, etc., interfaces. Design/methodology/approach -A three-dimensional ellipsoidal discrete element method (DEM) is developed to more physically represent particle shape in granular media while retaining the efficiency of smooth contact interface conditions for computation. DE coupling to finite element (FE) facets is presented to demonstrate initially the development of overlapping bridging scale methods for concurrent multiscale modeling of granular media. Findings -A closed-form solution of ellipsoidal particle contact resolution and stiffness is presented and demonstrated for two particle, and many particle contact simulations, during gravity deposition, and quasi-static oedometer, triaxial compression, and pile penetration. The DE-FE facet coupling demonstrates the potential to alleviate artificial boundary effects in the shear deformation region between DEM granular media and deformable solid bodies.Research limitations/implications -The research is being extended to couple more robustly the ellipsoidal DEM code and a higher order continuum FE code via overlapping bridging scale methods, in order to remove dependence of penetration/shear resistance on the boundary placement for DE simulation. Practical implications -When concurrent multiscale computational modeling of interface conditions between deformable solid bodies and granular materials reaches maturity, modelers will be able to simulate the mechanical behavior accounting for physical particle sizes and flow in the interface region, and thus design their tool, tire, penetrometer, or pile accordingly. Originality/value -A closed-form solution for ellipsoidal particle contact is demonstrated in this paper, and the ability to couple DE to FE facets.

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

“…are far from spherical. DEM's lack of ability to capture particle shape has spurred the development of variants able to capture particle shape, ranging from sphere clumping [20] to polyhedra [22] to ellipsoids [46,59] to NURBS [35]. While clumping-and polyhedra-based methods can approximate the volume and general shape of sand particles, it has been shown experimentally and computationally that not only do the overall shape of particles ("sphericity") affect bulk granular behavior, but surface curvature at a lower, local scale ("roundness") also affects behavior [10,26].…”

Concurrent Multiscale Computational Modeling for Dense Dry Granular Materials Interfacing Deformable Solid Bodies

“…This is the overall goal of the research. An outline of the remainder of the chapter is as follows: section 2 provides a literature review; 3 a summary of balance equations for a particle and micropolar continuum representation of a granular material and their coupling [2]; 4 a method for coupling DE to FE facets [3] and numerical example; 5 a summary; and 6 mention of ongoing and future work.…”

A coupled distinct lattice spring model for rock failure under dynamic loads

“…In these models, the microscopic model is the particle based discrete model and the macroscopic continuum model utilized is typically the Finite Element Method (FEM) e.g. [16][17][18][19][20]. The coupling of the Discrete Element Method (DEM) and the FEM emerged in the late 1980s and several different models were proposed, e.g.…”

“…12.006 between the FEM block domain and particles around the interface. For example, Onate and Rojek [16] developed a contact algorithm in their model, Yan et al [17] used the ghost particle method, Lei and Zang [20] used a penalty function method and Elmekati and Shamy [18] and Cai et al [24] used the contact function provided in commercial codes to undertake a coupled analysis of geotechnical systems. Another recently developed approach is the use of a bridging domain to link two different scale models [19]; this coupling technique is called the bridging domain method, which was first developed by Xiao and Belytschko [25] for coupling Molecular Dynamics (MD) and FEM.…”

“…Moreover, in most coupled models (e.g. [16][17][18][19][20]), the microscopic and macroscopic domains remain unchanged during the computational process and transition from macroscopic level to microscopic model is not considered.…”