An improved specimen generation method for DEM based on local Delaunay tessellation and distance function

Abstract

SUMMARYDiscretizing a domain of interest into a set of particles for discrete element simulation is the first step to generate a specimen. An improved algorithm, the Seed Expansion Method (SEM), is proposed in this work. A seed is first generated inside a given domain. Then, the domain is filled by the seed expansion based on a local Delaunay tessellation and a distance function. An optional operation, refilling, is suggested to further improve the packing density after the completion of SEM. Polydisperse dense packing can be generated by the proposed method for an arbitrarily shaped domain in both 2D and 3D. A specimen can be obtained that approximately conforms to a specified size distribution and packing density. Multiple subdomains of a domain can be filled by packings with different densities and size distributions. A specimen with higher density can be obtained by comparing it with the existing methods. Mathematically, the features of the method include both simplicity and high efficiency.

Numerical modeling of rock fracture and fragmentation under impact loading using discrete element method

“…17 The specimens used in the two simulations were generated by the SEM. 17 Seeds were first generated inside a given boundary, which include four spheres. The bases, which include three spheres, can be obtained by local Delaunay tessellation, which serve to generate new spheres by a simple algebraic calculation.…”

An efficient dense and stable particular elements generation method based on geometry

“…Subsequently, particles with radii located in a preset interval were used for filling the domain to obtain denser packings and packings with larger coordinate number . Recently, increasing numbers of research studies are inclined to seek an efficient method that can fill a given geometry with a lower porosity and a larger coordinate number .…”

“…Thus, the geometry‐based generation methods are more popular. There are mainly three types of geometric constructive methods: the grid‐based method , the triangular or tetrahedral mesh‐based method , and the pure geometry method . The grid‐based method is efficient and can fill the domain with small porosity when the ratio of the maximum radius to the minimum radius, that is, the size ratio is large.…”

An Algorithm to Generate Random Sphere Packs in Arbitrary Domains

“…The quality analysis of the generated assemblies is based on conventional geometric properties also presented in (20,6,28,24). …”

“…For general domains the creation of the sphere pack may be complex and time consuming specially if the arrangement must comply with accuracy and stability requirements of the simulation (40). Many factors influence a simulation (28), some of which are: the radial distribution of the particles, the overlaps between them and the density ratio. This last property depends on the type of material; concrete, rock and ceramic require a high density pack while soil for example requires a lower density pack.…”