Skip to main content
SpringerLink
Log in

GPU-based collision analysis between a multi-body system and numerous particles

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

The use of a graphics processing unit (GPU) is an ideal solution for problems on data-parallel computations. The serial CPU-based program for collision analysis between a multi-body system and numerous particles is rebuilt as a parallel program that uses the advantages of a GPU. In this study, a GPU is used to effectively perform multi-body dynamic simulation with particle dynamics. The multibody system has 20 circular objects, 19 spring-damper force elements, and 2 revolute joints. The motion equations are formulated using the Cartesian coordinate system, and the implicit Hilber-Hughes-Taylor integration algorithm is used for the integral equation. To detect collisions between a multi-body system and particles or between particles, a spatial subdivision algorithm and a discrete element modeling are used. The developed program is verified by comparing the results with ADAMS. The numerical efficiencies of the serial program using CPU and the parallel program using GPU are compared according to the number of particles. The results show that the greater the number of particles, the more computing time can be saved. For example, when the number of particles is 900, the computing speed of the parallel analysis program is about five times faster than that of the serial analysis program.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. NVIDIA CUDA ™, NVIDIA CUDA C Programming Guide, Version 4.1, 2011-11-18.

  2. NVIDIA CUDA ™, CUDA Toolkit 4.1 CUBLAS Library, PG-05326-041_v01, October (2011).

    Google Scholar 

  3. EM Photonics, Inc., CULA Reference Manual, Release R13(CUDA4.0), November 08 (2011).

    Google Scholar 

  4. J. Sanders and E. Kandrot, CUDA by examples: An introduction to general-purpose GPU programming, Addison Wesley (2011).

    Google Scholar 

  5. D. Negrut, A. Tasora, M. Anitescu, H. Mazhar, T. Heyn and A. Pazouki, Solving large multibody dynamics problems on the GPU, Math, and Comp. Science Division, ANL/MCSP1777-0710 (2010).

    Google Scholar 

  6. A. Tasora, D. Negrut and M. Anitescu, GPU-based parallel computing for the simulation of complex multibody systems with unilateral and bilateral constraints: An overview.

  7. S. L. Grand, Broad-phase collision detection with CUDA, GPU GEMS 3, Addison Wesley (2007).

    Google Scholar 

  8. S. Green, Particle simulation using CUDA, NVIDIA Corporation (2010).

    Google Scholar 

  9. M. Tupy, A study on the dynamics of granular material with a comparison of DVI and DEM approaches, University of Wisconsin-madison (2010).

    Google Scholar 

  10. P. E. Nikravesh, Computter-aided analysis of mechanical systems, Prentice-Hall International. Inc.

  11. A. A. Shabana, Computational dynamics, 2 Ed. Wiley-Interscience (2001).

    MATH  Google Scholar 

  12. D. Negrut, R. Rampalli, G. Ottarsson and A. Sajdak, On the use of the HHT method in the context of index 3 differencial algebraic equations of multibody dynamics, International Journal for Numerical Methods in Engineering (2000) 00:1–6.

    Google Scholar 

  13. D. Negrut, G. Ottarsson, R. Rampalli and A. Sajdak, On an implementation of the Hilber-Hughes-Taylor method in the context of index 3 differential-algebraic equations of multibody dynamics, International Journal for Numerical Methods in Engineering (2002).

    Google Scholar 

  14. N. Schafer and D. Negrut, On the potential of implicit integration methods for molecular dynamics simulation, Journal of Computational Physics (2009).

    Google Scholar 

  15. MSC Software ADAMS help, MSC Software.

Download references

Author information

Authors and Affiliations

  1. Graduate School of Mechatronics Engineering, Pukyong National University, Busan, 608-739, Korea

    Hye-Young Jung & Chul-Woong Jun

  2. Department of Mechanical and Automotive Engineering, Pukyong National University, Busan, 608-739, Korea

    Jeong-Hyun Sohn

Authors
  1. Hye-Young Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chul-Woong Jun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jeong-Hyun Sohn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeong-Hyun Sohn.

Additional information

Recommended by Editor Yeon June Kang

Jeong-Hyun Sohn has been an associate professor in the Department of Mechanical and Automotive Engineering of Pukyong National University since 2003. His interests are multi-body system dynamics, mechanism design, and dynamic analysis of vehicle system.

Chul-Woong Jun is a graduate student of mechatronics engineering at Pukyong National University. His interests are parallel computing, high-performance computing, and multi-body system dynamics.

Hye-young Jung is a graduate student of mechatronics engineering at Pukyong National University. Her interests are kinematic design and dynamic analysis of mechanical systems.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jung, HY., Jun, CW. & Sohn, JH. GPU-based collision analysis between a multi-body system and numerous particles. J Mech Sci Technol 27, 973–980 (2013). https://doi.org/10.1007/s12206-013-0226-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-013-0226-4

Keywords

Search

Navigation