Advertisement

Examples for Modelling, Simulation and Visualization with the Discrete Element Method in Mechanical Engineering

  • Florian Fleissner
  • Peter Eberhard

In geo-physics, mining, civil and chemical engineering the Discrete Element Method (DEM) is a well established tool for physicists and engineers. It is used to simulate particle flows of granules and powders and to investigate shear effects and the nature of granular packings. In contrast to most other methods from the growing group of meshless methods, which are mainly designed to simulate continuum effects described by partial differential equations, the DEM accounts for the simulation of inter-particle contacts. In mechanical engineering the method can be used to simulate the effects of abrasive material in gears and engines that can lead to clamping and plugging. To gain insight into devices and observe the different particle flow phenomena, virtual reality is a powerful engineering tool. It enables the engineer to observe effects from the optimal point of view with an enhanced feeling for motion in restricted space due to its three dimensional view. For an optimal evaluation of simulation results in virtual reality environments, visualization techniques have to be chosen which are suited for the phenomena in focus.

Keywords

Virtual Reality Smooth Particle Hydrodynamic Discrete Element Method Multibody System Smooth Particle Hydrodynamic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Fleißner F, Gaugele T, Eberhard P (2007) Applications of the discrete element method in mechanical engineering. Multibody System Dynamics, accepted for publication, 2007.Google Scholar
  2. 2.
    Hairer E, Wanner G (1991) Solving Ordinary Differential Equations II - Stiff and Differential-Algebraic Problems. Springer, BerlinzbMATHGoogle Scholar
  3. 3.
    Hairer E, Wanner G (1999) Stiff differential equations solved by Radau methods. Journal of Computational and Applied Mathematics, 111:93-111zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Lankarani HM, Nikravesh PE (1990) A contact force model with hysteresis damping for impact analysis of multibody systems. Journal of Mechanical Design, 112:369-376CrossRefGoogle Scholar
  5. 5.
    Lorensen WE, Cline HE (1987) Marching cubes: A high resolution 3d surface construction algorithm. Computer Graphics, 21(4)Google Scholar
  6. 6.
    Monaghan JJ (1992) Smoothed particle hydrodynamics. Annual Reviews in Astronomy and As-trophysics, 30:543-574CrossRefGoogle Scholar
  7. 7.
    Petzold LR (1982) A description of DASSL: A differential/algebraic system solver. Technical Report SAND82-8637, Sandia National Laboratories, Livermore, CaliforniaGoogle Scholar
  8. 8.
    Schiehlen W (1990) Multibody Systems Handbook. Springer BerlinzbMATHGoogle Scholar
  9. 9.
    Schinner A (1999) Fast algorithms for the simulation of polygonal particles. Granular Matter, 2:35-43CrossRefGoogle Scholar
  10. 10.
    Shabana AA (2001) Computational Dynamics. John Wiley & Sons, New YorkzbMATHGoogle Scholar
  11. 11.
    Teschner M, Heidelberger B, Mueller M, Pomeranets D, Gross M (2003) Optimized spatial hashing for collision detection of deformable objects. In: Proceedings of Vision, Modeling, Visualization VMV’03, pp 47-54Google Scholar
  12. 12.
    Zwicker M, Pfister H, van Baar J, Gross M (2001) Surface splatting. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp 371-378Google Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Florian Fleissner
    • 1
  • Peter Eberhard
    • 1
  1. 1.Institute of Engineering and Computational MechanicsUniversity of Stuttgart PfaffenwaldringGermany

Personalised recommendations