Truncation error propagation in model order reduction techniques based on substructuring.

  • Alexander M. Steenhoek
  • Daniel J. Rixen
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


Several model order reduction techniques split a system in components after which these are reduced individually, where the dynamic response of individual components is typically approximated with a modal truncation of component modes. By an appropriate selection (which usually means selecting enough modes) the truncation error is expected to decrease, but generally no guarantee for the associated error found after reassembling the reduced component models into a single reduced model can be given. In this contribution we investigate how the truncation error arising from the applied reduction techniques for a separate component, propagates to the assembled models. This gives insight on how accurate the model description of separate component needs to be to obey a global overall accuracy of the assembled reduced model and can lead to a different selection criterium for the reduced model. This work is based on an error estimator for modal truncation and the work by Voormeeren [1] on error propagation techniques.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    SN Voormeeren, D. de Klerk, and DJ Rixen. Uncertainty quantification in experimental frequency based substructuring. Mechanical Systems and Signal Processing, 24(1):106–118.Google Scholar
  2. 2.
    W. Gawronski. Advanced structural dynamics and active control of structures. Springer Verlag, 2004.Google Scholar
  3. 3.
    A.C. Antoulas. Approximation of large-scale dynamical systems. Society for Industrial Mathematics, 2005.Google Scholar
  4. 4.
    S. Skogestad and I. Postlethwaite. Multivariable Feedback Control. Wiley, 1996.Google Scholar
  5. 5.
    D. de Klerk, DJ Rixen, and SN Voormeeren. General framework for dynamic substructuring: history, review, and classification of techniques. AIAA JOURNAL, 46(5):1169, 2008.Google Scholar
  6. 6.
    D de Klerk. Dynamic Response Characterization of Complex Systems through Operational Identification and Dynamic Substructuring. Phd Thesis, Delft, The Netherlands, 2009.Google Scholar
  7. 7.
    M. Géradin and D. Rixen. Mechanical vibrations. Wiley, 1997.Google Scholar

Copyright information

© Springer Science+Businees Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Precision and Microsystems EngineeringDelft University of TechnologyDelftThe Netherlands

Personalised recommendations