A comparison of data structures for the simulation of polydisperse particle packings

Simulation of particle packings is an important tool in material science. Polydisperse mixtures require huge sample sizes to be representative. Simulation, in particular with iterative packing algorithms, therefore requires highly efficient data structures to keep track of particles during the packi...

Full description

Saved in:
Bibliographic Details
Published in:International journal for numerical methods in engineering 2011-02, Vol.85 (5), p.625-639
Main Authors: Raschdorf, S., Kolonko, M.
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Cross-disciplinary physics: materials science
rheology
data structure
Data structures
Exact sciences and technology
Granular solids
Iterative methods
loose octree
Material form
Materials science
Numerical analysis
Physics
polydisperse
Rheology
spatial index
sphere packing
Verlet list
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Simulation of particle packings is an important tool in material science. Polydisperse mixtures require huge sample sizes to be representative. Simulation, in particular with iterative packing algorithms, therefore requires highly efficient data structures to keep track of particles during the packing procedure. We introduce a new hybrid data structure for spherical particles consisting of a so‐called loose octree for the global spatial indexing and Verlet lists for the local neighbourhood relations. It is particularly suited for relocation of spheres and contact searches. We compare it to classical data structures based on grids and (strict) octrees. It is shown both analytically and empirically that our data structure is highly superior for packing of large polydisperse samples. Copyright © 2010 John Wiley & Sons, Ltd.
ISSN:0029-5981
1097-0207
1097-0207
DOI:10.1002/nme.2988