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Computational Stochastic Dynamics Based on Orthogonal Expansion of Random Excitations

  • X. Frank Xu
  • George Stefanou
Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 26)

Abstract

A major challenge in stochastic dynamics is to model nonlinear systems subject to general non-Gaussian excitations which are prevalent in realistic engineering problems. In this work, an n-th order convolved orthogonal expansion (COE) method is proposed. For linear vibration systems, the statistics of the output can be directly obtained as the first-order COE about the underlying Gaussian process. The COE method is next verified by its application on a weakly nonlinear oscillator. In dealing with strongly nonlinear dynamics problems, a variational method is presented by formulating a convolution-type action and using the COE representation as trial functions.

Keywords

Power Spectral Density Trial Function Polynomial Chaos Expansion Orthogonal Expansion White Noise Excitation 
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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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Civil, Environmental and Ocean EngineeringStevens Institute of TechnologyHobokenUSA
  2. 2.Institute of Structural Analysis & Antiseismic ResearchNational Technical University of AthensAthensGreece

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