Name
Abstract | ||
|---|---|---|
Particle-based methods based on material models using spheres can provide good approximations for many physical phenomena at both the micro and macroscales. The point of departure for the simulations, in general, is a dense arrangement of spherical particles (sphere pack) inside a given container. For generic domains, the generation of a sphere pack may be complex and time-consuming, especially if the pack must comply with a prescribed sphere size distribution and the stability requirements of the simulation. The primary goal of this paper is to present an efficient algorithm that is capable of producing packs with millions of spheres following a statistical sphere size distribution inside complex arbitrary domains. This algorithm uses a new strategy to ensure that the sphere size distribution is preserved even when large particles are rejected in the growing process. The paper also presents numerical results that enable an evaluation of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.camwa.2016.02.032 | Computers & Mathematics with Applications |
Keywords | Field | DocType |
Sphere packing,Advancing-front approach,Geometric algorithm,Distance field applications | Mathematical optimization,Mathematical analysis,Sphere packing,Algorithm,Bounding sphere,SPHERES,Particle,Mathematics,Physical phenomena | Journal |
Volume | Issue | ISSN |
71 | 8 | 0898-1221 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elias Lozano | 1 | 0 | 0.34 |
| Deane Roehl | 2 | 0 | 0.34 |
| Waldemar Celes Filho | 3 | 235 | 23.88 |
| Marcelo Gattass | 4 | 382 | 48.43 |