Skip to main content

A collaborative benchmarking framework for multibody system dynamics


Despite the importance given to the computational efficiency of multibody system (MBS) simulation tools, there is a lack of standard benchmarks to measure the performance of these kinds of numerical simulations. This works proposes a collaborative benchmarking framework to measure and compare the performance of different MBS simulation methods. The framework is made up of two main components: (a) an on-line repository of test problems with reference solutions and standardized procedures to measure computational efficiency and (b) a prototype implementation of a collaborative web-based application to collect, organize and share information about performance results in an intuitive and graphical form. The proposed benchmarking framework has been tested to evaluate the performance of a commercial MBS simulation software, and it proved to be an effective tool to collect and analyze information about the numerous factors which affect the computational efficiency of dynamic simulations of multibody systems.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6


  1. García de Jalón J, Bayo E (1994) Kinematic and dynamic simulation of multibody systems - the real-time challenge. Springer-Verlag, New York

    Google Scholar 

  2. Bae DS, Lee JK, Cho HJ, Yae H (2000) An explicit integration method for realtime simulation of multibody vehicle models. Comput Methods Appl Mech Eng 187:337–350

    MATH  Article  Google Scholar 

  3. Anderson KS, Critchley JH (2003) Improved ‘Order-N’ performance algorithm for the simulation of constrained multi-rigid-body dynamic systems. Multibody Syst Dyn 9:185–212

    MATH  Article  MathSciNet  Google Scholar 

  4. Anderson K, Mukherjee R, Critchley J, Ziegler J, Lipton S (2007) POEMS: parallelizable open-source efficient multibody software. Eng Comput 23:11–23

    Article  Google Scholar 

  5. Gonzalez M, Gonzalez F, Dopico D, Luaces A (2008) On the effect of linear algebra implementations in real-time multibody system dynamics. Comput Mech 41:607–615

    MATH  Article  Google Scholar 

  6. Gonzalez M, Dopico D, Lugrís U, Cuadrado J (2006) A benchmarking system for MBS simulation software: problem standardization and performance measurement. Multibody Syst Dyn 16:179–190

    MATH  Article  Google Scholar 

  7. Cuadrado J, Cardenal J, Morer P (1997) Modeling and solution methods for efficient real-time simulation of multibody dynamics. Multibody Syst Dyn 1:259–280

    MATH  Article  MathSciNet  Google Scholar 

  8. Cuadrado J, Cardenal J, Morer P, Bayo E (2000) Intelligent simulation of multibody dynamics: space-state and descriptor methods in sequential and parallel computing environments. Multibody Syst Dyn 4:55–73

    MATH  Article  Google Scholar 

  9. Hairer E, Nørsett SP, Wanner G (1987) Solving ordinary differential equations I. Nonstiff problems. Springer-Verlag, Berlin

    MATH  Google Scholar 

  10. Hairer E, Wanner G (1991) Solving ordinary differential equations II. Stiff and differential-algebraic problems. Springer-Verlag, Berlin

    MATH  Google Scholar 

  11. Becker C, Kilian S, Turek S (1999) Consequences of modern hardware design for numerical simulations and their realization in FEAST, Euro-Par’99, Parallel Processing. In: Proceedings of the 5th international Euro-Par conference. Lecture notes in computer science, vol 1685. pp 643–650

  12. Eichberger A, Fuhrer C, Schwertassek R (1993) The benefits of parallel multibody simulation and its application to vehicle dynamics. In: Advanced multibody system dynamics: simulation and software tools. Kluwer Academic Publishers, Dordrecht, pp 107–126

  13. Quaranta G, Masarati P, Mantegazza P (2002) Multibody analysis of controlled aeroelastic systems on parallel computers. Multibody Syst Dyn 8:71–102

    MATH  Article  Google Scholar 

  14. Duan S, Anderson KS (2000) Parallel implementation of a low order algorithm for dynamics of multibody systems on a distributed memory computing system. Eng Comput 16:96–108

    MATH  Article  Google Scholar 

  15. Glesner M, Kirschbaum A, Renner FM, Voss B (2002) State-of-the-art in rapid prototyping for mechatronic systems. Mechatronics 12:987–998

    Article  Google Scholar 

  16. Arnold M, Burgermeister B, Eichberger A (2007) Linearly implicit time integration methods in real-time applications: DAEs and stiff ODEs. Multibody Syst Dyn 17:99–117

    MATH  Article  MathSciNet  Google Scholar 

  17. MSC.Software Corporation (2004) ADAMS.

Download references


The authors gratefully acknowledge the support of the Spanish MEC under Grant No. DPI2003-05547-C02-01 and the Galician DGID under Grant No. PGIDT04PXIC16601PN.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Manuel González.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

González, M., González, F., Luaces, A. et al. A collaborative benchmarking framework for multibody system dynamics. Engineering with Computers 26, 1–9 (2010).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Multibody dynamics
  • Simulation
  • Performance
  • Efficiency
  • Benchmark
  • Web-based system