Title
Parallel Sphere Packing for Arbitrary Domains
Date Issued
2022
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Springer Science and Business Media Deutschland GmbH
Abstract
Particle packings are methods used to fill a container with particles. These are used to simulate granular matter, which has various uses. Particle packings seek to be dense, however, particle packings are slow, they don’t become completely dense, and most only work in simple containers. Currently, several techniques have been proposed to achieve a dense packing, significantly reducing packing construction time, but little progress has been seen in increasing the density of the packing. Particle packings reach an average maximum density of approximately 70% in rectangular and cylindrical containers, and 60% in arbitrary containers. The density of the packings is also known as compaction or solid fraction. The objective of this work is to make a compact packing that in arbitrary containers reaches between 60% and 70% of compaction. For this, a compact periodic packing of spheres is taken as a basis, which from the use of spheres of the same size achieves the highest compaction, that is, it is the most dense. Searched packing is made following a periodic hexagonal pattern, to this are added three sizes of spheres, which are smaller than the initial size, these spheres go in the empty spaces left by the hexagonal packing. The proposed method, reaches densities in arbitrary containers between 60% and 70% in times less than 5 min using a parallel optimization on GPU resource.
Start page
447
End page
460
Volume
13018 LNCS
Language
English
OCDE Knowledge area
Ciencias de la computación
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
0302-9743
ISBN of the container
978-303090435-7
Conference
16th International Symposium on Visual Computing, ISVC 2021
Sponsor(s)
Acknowledgements. M. E. LOAIZA acknowledges the financial support of the CON-CYTEC – BANCO MUNDIAL Project “Mejoramiento y Ampliación de los Servi-cios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit PROCIENCIA, within the framework of the call E041-01, Contract No. 038-2018-FONDECYT-BM-IADT-AV.
Sources of information: Directorio de Producción Científica Universidad Católica San Pablo