Stochastic models of chaotic systems

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Nonlinear dynamical systems, although strictly deterministic, often exhibit chaotic behavior which appears to be random. The determination of the probabilistic properties of such systems is, in general, an open problem. Closure approximations for moment expansion methods have been unsatisfactory. More successful has been approximation on the dynamics level by the use of linear stochastic models that attempt to generate the probabilistic properties of the original nonlinear chaotic system as closely as possible. Examples are reviewed of this approach to simple nonlinear systems, to turbulence, and to large-eddy simulation. A stochastic model that simulates the transient energy spectrum of the global ... continued below

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21 p.

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Leith, C.E. September 1, 1995.

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Description

Nonlinear dynamical systems, although strictly deterministic, often exhibit chaotic behavior which appears to be random. The determination of the probabilistic properties of such systems is, in general, an open problem. Closure approximations for moment expansion methods have been unsatisfactory. More successful has been approximation on the dynamics level by the use of linear stochastic models that attempt to generate the probabilistic properties of the original nonlinear chaotic system as closely as possible. Examples are reviewed of this approach to simple nonlinear systems, to turbulence, and to large-eddy simulation. A stochastic model that simulates the transient energy spectrum of the global atmosphere is developed.

Physical Description

21 p.

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OSTI as DE96007545

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  • Nonlinear phenomena in ocean dynamics, Los Alamos, NM (United States), 15-19 May 1995

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  • Other: DE96007545
  • Report No.: UCRL-JC--122213
  • Report No.: CONF-9505328--1
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 204648
  • Archival Resource Key: ark:/67531/metadc670974

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  • September 1, 1995

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  • June 29, 2015, 9:42 p.m.

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  • Feb. 17, 2016, 5:59 p.m.

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Leith, C.E. Stochastic models of chaotic systems, article, September 1, 1995; California. (digital.library.unt.edu/ark:/67531/metadc670974/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.