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Virtual Prototypes for Uncertainty and Variability-Based Product Engineering

  • Roberto d'Ippolito
  • Stijn Donders
  • Herman Van der Auweraer

Product designers worldwide are confronted with highly competitive though conflicting demands to deliver more complex products with increased quality in ever shorter development cycles. Optimizing design performance with purely test-based approaches is no longer an option and numerical simulation methods are widely used to model, assess and improve the product design based on virtual prototypes. Functional performance attributes such as body strength, NVH, VAM, durability, crashworthiness … [3, 9, 22] can already be optimized before entering the expensive test phase. A new paradigm of mechanical testing as essential enabler in the virtual prototype optimization process resulted. Combined advances in test and simulation push the design envelope to shorter and higher quality product development cycles [21].

The use of the Finite Element (FE) method is widely established for the virtual prototyping phase. A major issue is the presence of uncertainty and variability in the material and geometrical properties and manufacturing processes [18, 26]; their effect on the performance cannot be predicted from a single FE analysis.

Keywords

Limit State Function Virtual Prototype First Order Reliability Method Design Sensitivity Analysis Response Surface Methodology Model 
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.

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References

  1. 1.
    Arimoto H, Yasuki T, Kouji K, Kondou M (1998) A Study on EnergyAbsorbing Mechanism of Plastic Ribs, 16th Annual brake Colloquium and Engineering Display, San Francisco, California, September 20-23, 1998.Google Scholar
  2. 2.
    Barkey M, Hack M, Speckert M,  Zingsheim F,  Schäfer G (2002) LMS.FALANCS Theory Manual, LMS Deutschland GmbH, Luxemburger Straße 7, D-67657 Kaiserslautern, Germany.Google Scholar
  3. 3.
    Bäcker M, Langthaler Th, Olbrich M, Oppermann H (2005) The hybrid road approach for durability loads prediction, SAE paper 2005-01-0628.Google Scholar
  4. 4.
    Dassault Systèmes, “CATIA”, V5R17, August 2006.Google Scholar
  5. 5.
    d’Ippolito R, Donders S, Hack M, Tzannetakis N, Van der Linden G, Vandepitte D (2006) Reliability-based design optimization of composite and steel aerospace structures, Proc. 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Newport, Rhode Island, USA, May 1-4, 2006.Google Scholar
  6. 6.
    d’Ippolito R, Hack M, Donders S, Hermans L (2006) A reliability analysis approach to improve the fatigue life of a vehicle knuckle, Proc. RASD 2006, Southampton, UK, July 17-19, 2006Google Scholar
  7. 7.
    Haque E, Kamarajan J, Yang G (2000) Development and Characterization of New Headliner Material to Meet FMVSS 201 Requirements, SAE World Congress, Detroit, MI, March 2000Google Scholar
  8. 8.
  9. 9.
    Jans J, Wyckaert K, Brughmans M, Kienert M, Van der Auweraer H, Donders S, Hadjit R (2006) Reducing Body Development Time by Integrating NVH and Durability Analysis from the Start, 2006-01-1228, Proc. SAE 2006 World Congress, Detroit, MI, USA, April 3-6, 2006.Google Scholar
  10. 10.
    Khuri AI, Cornell JA (1996) Response Surfaces, Design and Analysis, Marcel Dekker, Inc., New York, USA, second edition.Google Scholar
  11. 11.
    Kim UG, Kang S (2001) Optimum design of an A-pillar trim with rib structures for occupant head protection, IMechE Conference 2001.Google Scholar
  12. 12.
    LMS International, “LMS Virtual.Lab”, Rev 6B, November 2006.Google Scholar
  13. 13.
    Lorenzen TJ, Anderson VL (1993) Design of Experiments, a no-name approach, Marcel Dekker, Inc., New York, USA.MATHGoogle Scholar
  14. 14.
    LS-DYNA3D, commercial CAE software for high speed dynamic FEA analysis from LSTC CorpGoogle Scholar
  15. 15.
    Melchers RB (1999) Structural Reliability Analysis and Prediction, 2nd Edition.Google Scholar
  16. 16.
    Mourelatos Z, Liang J (2005) A Reliability-Based Robust Design Methodology, SAE 2005-01-0811, Proc. SAE World Congress, Detroit, MI, US, April 2005.Google Scholar
  17. 17.
    Noesis Solutions, OPTIMUS, Rev. 5.2, September 2006.Google Scholar
  18. 18.
    Oberkampf W. et al. (1998) Variability, Uncertainty and Error in Computational Simulation, AIAA/ASME Joint Thermophysics and Heat Transfer Conference, ASME-HTD-Vol. 357-2, pp 259-272.Google Scholar
  19. 19.
    Schuëller GI, Pradlwarter HJ, Koutsourelakis PS (2004) A Critical appraisal of reliability estimation procedures for high dimensions, Probabilistic Engineering Mechanics, Vol. 19, pp 463-474.CrossRefGoogle Scholar
  20. 20.
    Sudret B, Der Kiureghian A (2000) Stochastic Finite Element Methods and Reliability, A state of the art report, UCB/SEMM-2000/08 Dept. of Civil and Environmental Engineering, University of California, Berkley, November 2000.Google Scholar
  21. 21.
    Van der Auweraer H, Leuridan J (2004) The New Paradigm of Testing in Today’s Product Development Process, Proc. ISMA 2004, Leuven, Belgium, Sept. 20-22, pp 1151-1170.Google Scholar
  22. 22.
    Van der Auweraer H, Tournour M, Wyckaert K, De Langhe K (2005) VibroAcoustic CAE from an Industrial Application Perspective, SAE paper SIAT2005-0157, Proc. SIAT 2005 conference, Pune, India, Jan. 19.Google Scholar
  23. 23.
    Van der Auweraer H, Van Langenhove T, Brughmans M, Bosmans I, El Masri N, Donders S (2007) Application of Mesh Morphing Technology in the Concept Phase of Vehicle Development, Int. J. of Vehicle Design, Computer Aided Automotive Development, in press.Google Scholar
  24. 24.
    Vecchio A, Carmine R, De Voghel R, Van der Linden G, Guillaume P (2003) Numerical Evaluation of Damage Distribution over a Slat Track Using Flight Test Data, Proc. IMAC XXI, Orlando, FL, USA.Google Scholar
  25. 25.
    Youn BD, Choi KK, Park YH (2003) Hybrid Analysis Method for ReliabilityBased Design Optimization, Journal of Mechanical Design, ASME, Vol. 125, pp 221-232, June 2003.CrossRefGoogle Scholar
  26. 26.
    Zang TA et al. (2002) Needs and Opportunities for Uncertainty-based Multidisciplinary Design Methods for Aerospace Vehicles, NASA/TM-2002-211462.Google Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Roberto d'Ippolito
    • 1
  • Stijn Donders
    • 1
  • Herman Van der Auweraer
    • 1
  1. 1.LMS InternationalBelgium

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