DEM stands for Discrete Element Method.
Wikipedia article on DEM
WHAT IS LIGGGHTS?
LIGGGHTS is an Open Source Discrete Element Method Particle Simulation Software.
LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations.
LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics. Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kind of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications.
Slide material: A recent presentation at the CFD2011 conference in Trondheim can be found here. A keynote presentation of LIGGGHTS at the 2nd LAMMPS workshop hosted by Sandia Labs, Albuquerque, can be found here: "Enhancing LAMMPS Capabilities: Granular Models, Coding Concepts, CAD Interoperability and Coupling to Continuum Methods". More info on the workshop in general see here.
The features added in LIGGGHTS with respect to the original LAMMPS distribution comprise:
+ Import and handling of complex wall geometries from CAD
+ A moving mesh feature to account for moving geometry
+ Re-write of contact force formulation, including optional cohesional and rolling friction forces
+ Heat conduction between particles in contact
+ Improved particle insertion based on surface and volume meshes
+ A "template" mechanism to account for particle non-uniformity
+ More features added in the meantime and upcoming, see here.
Of course, LIGGGHTS inherits all the abilities the standard LAMMPS distribution offers for the simulation of granular materials:
+ An easy-to-understand structure of the code
+ A flexible scripting language allowing efficient usage
+ Efficient parallelization
+ The basics of the GRANULAR package, like particle insertion, shear history implementation
+ Electrostatic forces
+ Molecular Dynamics
+ Post-processing
LIGGGHTS and it's post-processing tools are developed, distributed and maintained by our team, with major contributions from:
Christoph Kloss,
Philippe Seil,
Stefan Amberger, and
Andreas Aigner.
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