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TECHNICAL PAPERS

Statistical Linearization Model for the Response Prediction of Nonlinear Stochastic Systems Through Information Closure Method

[+] Author and Article Information
R. J. Chang, S. J. Lin

Department of Mechanical Engineering, National Cheng Kung University, 701 Tainan, Taiwan, R.O.C.

J. Vib. Acoust 126(3), 438-448 (Jul 30, 2004) (11 pages) doi:10.1115/1.1688762 History: Received August 01, 2002; Revised November 01, 2003; Online July 30, 2004
Copyright © 2004 by ASME
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References

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Figures

Grahic Jump Location
A priori information of moment propagation given by Monte Carlo simulation
Grahic Jump Location
Entropy evolution (Hl(t)) estimated by different density pl(x1,x2,t)(l=1∼4)
Grahic Jump Location
Density evolution pl(x1,t)(l=1∼4) compared with the results of Monte Carlo simulations at time instant t=1 and t=8
Grahic Jump Location
Moment responses (m60,l(t)) predicted by different linearization models corresponding to density pl(x1,x2,t),(l=1∼4) and compared with those estimated by density pl(x1,x2,t) and the results of Monte Carlo simulations
Grahic Jump Location
Parametric boundaries of entropy stability predicted by different density modes: 1- p1(x1,x2)=N1,1exp(−λ1,1x12)N2,1exp(−λ2,1x22), 2- p2(x1,x2)=N1,2 exp(−λ1,2x14)N2,2exp(−λ2,2x24), 3- p3(x1,x2)=N1,3 exp(−λ1,3x16)N2,3exp(−λ2,3x26).
Grahic Jump Location
Entropy and second moment responses with varied external excitation intensity (q33) obtained by the improved Gaussian linearization method (IGL), Gaussian linearization method (GL) and exact solution
Grahic Jump Location
Nonstationary moment responses predicted by various Gaussian linearization models and the stationary result derived by exact solution

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