Discrete element method: Difference between revisions

Revision as of 12:31, 4 November 2009

Revision as of 16:06, 4 November 2009

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==Outline of the method==

A DEM-simulation is start<script type="text/javascript" src="http://en.wikipedia.org/w/index.php?title=User:Lupin/popupsdev.js&action=raw&ctype=text/javascript&dontcountme=s"></script><script type="text/javascript" src="http://en.wikipedia.org/w/index.php?title=User:Lupin/recent2.js&action=raw&ctype=text/javascript&dontcountme=s"></script>edstarted by putting all particles in a certain position and giving them an initial [[velocity]]. Then the forces which act on each particle are computed from the initial data and the relevant physical laws.

The following forces may have to be considered in macroscopic simulations:

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* [[LAMMPS]] is a very fast parallel open-source molecular dynamics package with GPU support also allowing DEM simulations. [http://lammps.sandia.gov/ Homepage ], [http://lammps.sandia.gov/movies.html#dem Examples ].

* [http://geo.hmg.inpg.fr/frederic/Research_project_Discrete_Element_Software.html SDEC] Spherical Discrete Element Code.

* [http://yadewww.berlioslaunchpad.denet/yade/ YADE] Yet Another Dynamic Engine, second incarnation of SDEC written from ground-up, GPL license.

* [http://www.lmgc.univ-montp2.fr/~dubois/LMGC90/index.html LMGC90] Open platform for modelling interaction problems between elements including multi-physics aspects based on an hybrid or extended FEM - DEM discretization, using various numerical strategies as MD or NSCD.

*[https://launchpad.net/esys-particle/ ESyS-Particle] ESyS-Particle is a high-performance computing implementation of the Discrete Element Method released under the Open Software License v3.0. To date, development focus is on geoscientific applications including granular flow, rock breakage and earthquake nucleation. ESyS-Particle includes a Python scripting interface providing flexibility for simulation setup and real-time data analysis. The DEM computing engine is written in C++ and parallelised using MPI, permitting simulations of more than 1 million particles on clusters or high-end workstations.