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Particle-Based Simulation of Granula...

Tananuchittikul, Rachan.

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Particle-Based Simulation of Granular Materials on GPUs.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Particle-Based Simulation of Granular Materials on GPUs./
Author:	Tananuchittikul, Rachan.
Description:	102 p.
Notes:	Source: Masters Abstracts International, Volume: 49-03, page: .
Contained By:	Masters Abstracts International49-03.
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1487612
ISBN:	9781124405308

Particle-Based Simulation of Granular Materials on GPUs.
Tananuchittikul, Rachan.

Particle-Based Simulation of Granular Materials on GPUs. - 102 p.

Source: Masters Abstracts International, Volume: 49-03, page: .

Thesis (M.S.)--California State University, Fullerton, 2011.

Simulating granular material has been a challenging topic in the field of computer graphics because grain can generate different interesting phenomena like avalanche and heap. A numerical method known as discrete element method or distinct element method (DEM) is preferable technique to simulate granular material on a discrete machine or computer. To get a realistic outcome, a large number of particles are required and that will result in a slow simulation. Since in a simulation time step each particle of DEM system can be processed spontaneously, running this type of simulation on the graphic process units (GPU) shall produce the same result with a smaller time spent. This paper presents particle-based simulation of the granular material on the GPU. Grains and other objects in the simulation are approximated by the combination of uniform spherical particles. A grain element is modeled as a rigid body which composes of four particles arranged in a tetrahedral structure. The interaction between the particles is derived from sphere-sphere penetrations. Nonlinear spring force based on Hertz model is applied for the contact force. Uniform grid data structure is used to reduce the searching time for all the collisions in a time step. We discuss different techniques for simulating grain on the GPU, either in flavor of accuracy or speed. At the very end, we also provide the comparison among different settings of the simulation.

ISBN: 9781124405308Subjects--Topical Terms:

1669061
Engineering, Computer.

Particle-Based Simulation of Granular Materials on GPUs.
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100 1 $a Tananuchittikul, Rachan. $3 1672412
245 1 0 $a Particle-Based Simulation of Granular Materials on GPUs.
300 $a 102 p.
500 $a Source: Masters Abstracts International, Volume: 49-03, page: .
500 $a Adviser: Michael Shafae.
502 $a Thesis (M.S.)--California State University, Fullerton, 2011.
520 $a Simulating granular material has been a challenging topic in the field of computer graphics because grain can generate different interesting phenomena like avalanche and heap. A numerical method known as discrete element method or distinct element method (DEM) is preferable technique to simulate granular material on a discrete machine or computer. To get a realistic outcome, a large number of particles are required and that will result in a slow simulation. Since in a simulation time step each particle of DEM system can be processed spontaneously, running this type of simulation on the graphic process units (GPU) shall produce the same result with a smaller time spent. This paper presents particle-based simulation of the granular material on the GPU. Grains and other objects in the simulation are approximated by the combination of uniform spherical particles. A grain element is modeled as a rigid body which composes of four particles arranged in a tetrahedral structure. The interaction between the particles is derived from sphere-sphere penetrations. Nonlinear spring force based on Hertz model is applied for the contact force. Uniform grid data structure is used to reduce the searching time for all the collisions in a time step. We discuss different techniques for simulating grain on the GPU, either in flavor of accuracy or speed. At the very end, we also provide the comparison among different settings of the simulation.
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710 2 $a California State University, Fullerton. $3 1017845
773 0 $t Masters Abstracts International $g 49-03.
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