Time-saving Robust Design Considering Vehicle Crash Performance

  • Axel Schumacher
Conference paper


In this contribution, a time-saving robust design process is presented. The basic idea of this process is the calculation of the robust analyses based on generated response surface models. With these stochastic results, new response surfaces are created and are used for structural optimization. The efficiency of the process is shown with two application examples coming from the vehicle crash discipline. It is shown, that the method can handle large finite element models (>100k finite elements) in a limited time.


Design Variable Robust Optimization Response Surface Model Multidisciplinary Analysis Crash Simulation 
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  1. [1]
    DuBois, P.A. (2001): Crashworthiness Engineering with LS-DYNA, Seminar notes of the CADFEM-Seminar, Leinfelden/StuttgartGoogle Scholar
  2. [2]
    Marezyk, J. (1999): Principles of simulation-based computer-aided engineering, Artes Graficas Torres, Barcelona, Spain.Google Scholar
  3. [3]
    Holzner, M., Gholami, T., Mader, H.U. (1998): “The Virtual Crash Lab: Objectives, Requirements, and recent Developements”, VDI-Berichte 1411, VDI-Verlag, Düsseldorf (in German )Google Scholar
  4. [4]
    Schumacher, A., Hierold, R. (2000): parameterized CAD-models for multidisciplinary optimization processes", 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 6–8 September 2000, Long Beach, CA, AIAA2000-4912.Google Scholar
  5. [5]
    Schumacher, A., Brunies, F. (2000): “Crash Optimization considering Interdisciplinary structural requirements”, VDI-Berichte 1559, VDI-Verlag, Düsseldorf (in German )Google Scholar
  6. [6]
    Eschenauer, H.A., Vietor, T. (1992): “The efficiency of several methods in stochastic structural optimization”, ZAMM 72 (1992) 6, T570 - T573Google Scholar
  7. [7]
    Hunter, J.S. (1985): “Statistical Design Applied to Product Design”, J. of Quality Technology, Vol. 17, No. 4.Google Scholar
  8. [8]
    Tzannetakis, N., Van der Peer, J. (2000): “Making Optimization Practical for Industry through Approximation Methods. Software and Applications”, 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 6–8 September 2000, Long Beach, CA, AIAA2000-4936.Google Scholar
  9. [9]
    N.N. (2000): LS-DYNA User’s Manual, Livermore Software Technology Corporation, 2876 Waverley Way, Livermore, CA 94550-1740 U.S.A.Google Scholar
  10. [10]
    N.N. (2000): MSC/NASTRAN Online Encyclopedia, The MacNeal- Schwendler Corporation, 815 Colorado Boulevard, Los Angeles, CA, U.S.A.Google Scholar

Copyright information

© Springer-Verlag London Limited 2002

Authors and Affiliations

  • Axel Schumacher
    • 1
  1. 1.Adam Opel AG, IPC 80-40RüsselsheimGermany

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