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Probabilistic solutions of nonlinear oscillators excited by correlated external and velocity-parametric Gaussian white noises
Guo, S; Er, G. K.; Lam, C. C.
2014-08-01
Source PublicationNonlinear Dynamics
ISSN0924-090X
Pages597-604
Abstract

This paper addresses the random vibrations of the oscillators with correlated external and parametric excitations being Gaussian white noises. The exponential polynomial closure method is used in the analysis, with which the probability density of the system responses is obtained. Two oscillators are analyzed. One is about the linear oscillator subjected to correlated external and parametric excitations. Another is about the oscillator with cubic nonlinearity and subjected to correlated external and parametric excitations. Numerical studies show that exponential polynomial closure method provides computationally efficient and relatively accurate estimates of the stationary probabilistic solutions, particularly in the tail regions of the probability density functions.Numerical results further show that correlated external and parametric excitations can cause unsymmetrical probabilistic solutions and nonzero means which are different from those when the external and parametric excitations are independent.

KeywordCorrelated Excitations Exponential Polynomial Closure Method Nonzero Mean Fokker-planck-kolmogorov Equation
DOI10.1007/s11071-014-1322-4
Language英語English
The Source to ArticlePB_Publication
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Document TypeJournal article
CollectionDEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Recommended Citation
GB/T 7714
Guo, S,Er, G. K.,Lam, C. C.. Probabilistic solutions of nonlinear oscillators excited by correlated external and velocity-parametric Gaussian white noises[J]. Nonlinear Dynamics, 2014, 597-604.
APA Guo, S., Er, G. K.., & Lam, C. C. (2014). Probabilistic solutions of nonlinear oscillators excited by correlated external and velocity-parametric Gaussian white noises. Nonlinear Dynamics, 597-604.
MLA Guo, S,et al."Probabilistic solutions of nonlinear oscillators excited by correlated external and velocity-parametric Gaussian white noises".Nonlinear Dynamics (2014):597-604.
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