Uncertainty propagation in SEA using sensitivity analysis and Design of Experiments

  • Antonio Culla
  • Walter D’Ambrogio
  • Annalisa Fregolent
Part of the IUTAM Bookseries book series (IUTAMBOOK, volume 27)

Abstract

A limit of Statistical Energy Analysis (SEA) is that of providing only the mean values of the mechanical energy of a vibrating system. In the proposed paper, the variability of SEA solution under uncertain SEA parameters (coupling loss factors and internal loss factors) is investigated by comparing a sensitivity approach and a Design of Experiment (DoE) approach. Uncertainties of the SEA parameters depend on uncertainties in the physical properties of the considered mechanical system (Young modulus, material density, geometry, …). Numerical results are derived using a benchmark structure made by three aluminum plates with a common junction.

Keywords

Loss Factor Acoustical Society Modal Group Uncertainty Propagation Octave Band 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lyon, R., De Jong, R.: Theory and Applications of Statistical Energy Analysis. The MIT Press, Cambridge (U.S.A.) (1995) Google Scholar
  2. 2.
    Lyon, R.: Statistical analysis of power injection and response in structures and rooms. Journal of the Acoustical Society of America 45(3), 545–565 (1969) CrossRefGoogle Scholar
  3. 3.
    Radcliffe, C.J., Huang, X.: Putting statistics into the statistical energy analysis of automotive vehicles. Journal of Vibration and Acoustics 119(4), 629–634 (1997) CrossRefGoogle Scholar
  4. 4.
    Langley, R., Cotoni, V.: Response variance prediction in the statistical energy analysis of built-up systems. Journal of the Acoustical Society of America 115(2), 706–718 (2004) CrossRefGoogle Scholar
  5. 5.
    Weaver, R.: Spectral statistics in elastodynamics. Journal of the Acoustical Society of America 85, 1005–1013 (1989) CrossRefGoogle Scholar
  6. 6.
    Culla, A., Carcaterra, A., Sestieri, A.: Energy flow uncertainties in vibrating systems: Definition of a statistical confidence factor. Mechanical Systems and Signal Processing 17(3), 635–663 (2003) CrossRefGoogle Scholar
  7. 7.
    de Langhe, R.: Statistical analysis of the power injection method. Journal of the Acoustical Society of America 100(1), 294–304 (1996) CrossRefGoogle Scholar
  8. 8.
    Bussow, R., Petersson, B.: Path sensitivity and uncertainty propagation in SEA. Journal of Sound and Vibration 300(3–5), 479–489 (2007) CrossRefGoogle Scholar
  9. 9.
    Langley, R., Cotoni, V.: Response variance prediction for uncertain vibro-acoustic systems using a hybrid deterministic-statistical method. Journal of the Acoustical Society of America 122(6), 3445–3463 (2007) CrossRefGoogle Scholar
  10. 10.
    Montgomery, D.: Design and Analysis of Experiments, 6th edn. Wiley, New York (2005) MATHGoogle Scholar
  11. 11.
    D’Ambrogio, W., Fregolent, A.: Reducing variability of a set of structures assembled from uncertain substructures. In: Proceeding of 26th IMAC. Orlando (U.S.A.) (2008) Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Antonio Culla
    • 1
  • Walter D’Ambrogio
  • Annalisa Fregolent
  1. 1.Dipartimento di Meccanica e AeronauticaUniversità di Roma “La Sapienza”RomaItaly

Personalised recommendations