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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

Figures

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A priori information of moment propagation given by Monte Carlo simulation
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Entropy evolution (Hl(t)) estimated by different density pl(x1,x2,t)(l=1∼4)
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Density evolution pl(x1,t)(l=1∼4) compared with the results of Monte Carlo simulations at time instant t=1 and t=8
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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
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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).
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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
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Nonstationary moment responses predicted by various Gaussian linearization models and the stationary result derived by exact solution

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