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Characterization of Structural Dynamics With Uncertainty by Using Gaussian Processes

[+] Author Affiliations
Z. Xia, J. Tang

University of Connecticut, Storrs, CT

Paper No. DETC2011-48804, pp. 1225-1239; 15 pages
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 23rd Biennial Conference on Mechanical Vibration and Noise, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5478-5
  • Copyright © 2011 by ASME


An efficient way to capture the dynamic characteristics of structural systems with uncertainties has been an important and challenging subject. While such characterization is valuable for structural response predictions, it could be impractical in many application situations where a sufficiently large sample is expensive or unavailable. In this paper, Gaussian process regression models are employed to capture structural dynamical responses, especially responses with uncertainties. When Gaussian processes are used to make predictions for responses with uncertainties, the sampling costs can be significantly reduced because only a relatively small set of data points is needed. With no loss of generality, applications of Gaussian process regression models are introduced in conjunction with Monte Carlo sampling. This approach can be easily generalized to situations where data points are obtained by other sampling techniques.

Copyright © 2011 by ASME



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