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    Marginal Instability and Intermittency in Stochastic Systems—Part II: Systems With Rapid Random Variations in Parameters

    Source: Journal of Applied Mechanics:;2009:;volume( 076 ):;issue: 003::page 31002
    Author:
    M. F. Dimentberg
    ,
    A. Hera
    ,
    A. Naess
    DOI: 10.1115/1.3086593
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Dynamic systems with lumped parameters, which experience random temporal variations, are considered. The variations “smear” the boundary between the system’s states, which are dynamically stable and unstable in the classical sense. The system’s response within such a “twilight zone” of marginal instability is found to be of an intermittent nature, with alternating periods of zero (or almost-zero) response and rare short outbreaks. As long as it may be impractical to preclude completely such outbreaks for a designed system, subject to highly uncertain dynamic loads, the corresponding system’s response should be analyzed. Results of such analyses are presented for cases of slow and rapid (broadband) parameter variations in Papers I and II, respectively. The former case has been studied in Paper I (2008, “Marginal Instability and Intermittency in Stochastic Systems—Part I: Systems With Slow Random Variations of Parameters,” ASME J. Appl. Mech., 75(4), pp. 041002) for a linear model of the system using a parabolic approximation for the variations in the vicinity of their peaks (so-called Slepian model) together with Krylov–Bogoliubov averaging for the transient response. This resulted in a solution for the probability density function (PDF) of the response, which was of an intermittent nature indeed due to the specific algorithm of its generation. In the present paper (Paper II), rapid broadband parameter variations are considered, which can be described by the theory of Markov processes. The system is assumed to operate beyond its stochastic instability threshold—although only slightly—and its nonlinear model is used accordingly. The analysis is based on the solution of the Fokker–Planck–Kolmogorov partial differential equation for the relevant stationary PDF of the response. Several such PDFs are analyzed; they are found to have integrable singularities at the origin, indicating an intermittent nature of the response. Asymptotic analysis is performed for the first-passage problem for such response processes with highly singular PDFs, resulting in explicit formulas for an expected time interval between outbreaks in the intermittent response.
    keyword(s): Damping , Dynamic systems , Approximation , Equations , Formulas , Markov processes , Transients (Dynamics) , Probability , Stochastic systems , Stability , Stress , Partial differential equations , Oscillations , Computer simulation , Steady state , Algorithms AND Density ,
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      Marginal Instability and Intermittency in Stochastic Systems—Part II: Systems With Rapid Random Variations in Parameters

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    https://yetl.yabesh.ir/yetl1/handle/yetl/139738
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    contributor authorM. F. Dimentberg
    contributor authorA. Hera
    contributor authorA. Naess
    date accessioned2017-05-09T00:31:16Z
    date available2017-05-09T00:31:16Z
    date copyrightMay, 2009
    date issued2009
    identifier issn0021-8936
    identifier otherJAMCAV-26748#031002_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/139738
    description abstractDynamic systems with lumped parameters, which experience random temporal variations, are considered. The variations “smear” the boundary between the system’s states, which are dynamically stable and unstable in the classical sense. The system’s response within such a “twilight zone” of marginal instability is found to be of an intermittent nature, with alternating periods of zero (or almost-zero) response and rare short outbreaks. As long as it may be impractical to preclude completely such outbreaks for a designed system, subject to highly uncertain dynamic loads, the corresponding system’s response should be analyzed. Results of such analyses are presented for cases of slow and rapid (broadband) parameter variations in Papers I and II, respectively. The former case has been studied in Paper I (2008, “Marginal Instability and Intermittency in Stochastic Systems—Part I: Systems With Slow Random Variations of Parameters,” ASME J. Appl. Mech., 75(4), pp. 041002) for a linear model of the system using a parabolic approximation for the variations in the vicinity of their peaks (so-called Slepian model) together with Krylov–Bogoliubov averaging for the transient response. This resulted in a solution for the probability density function (PDF) of the response, which was of an intermittent nature indeed due to the specific algorithm of its generation. In the present paper (Paper II), rapid broadband parameter variations are considered, which can be described by the theory of Markov processes. The system is assumed to operate beyond its stochastic instability threshold—although only slightly—and its nonlinear model is used accordingly. The analysis is based on the solution of the Fokker–Planck–Kolmogorov partial differential equation for the relevant stationary PDF of the response. Several such PDFs are analyzed; they are found to have integrable singularities at the origin, indicating an intermittent nature of the response. Asymptotic analysis is performed for the first-passage problem for such response processes with highly singular PDFs, resulting in explicit formulas for an expected time interval between outbreaks in the intermittent response.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMarginal Instability and Intermittency in Stochastic Systems—Part II: Systems With Rapid Random Variations in Parameters
    typeJournal Paper
    journal volume76
    journal issue3
    journal titleJournal of Applied Mechanics
    identifier doi10.1115/1.3086593
    journal fristpage31002
    identifier eissn1528-9036
    keywordsDamping
    keywordsDynamic systems
    keywordsApproximation
    keywordsEquations
    keywordsFormulas
    keywordsMarkov processes
    keywordsTransients (Dynamics)
    keywordsProbability
    keywordsStochastic systems
    keywordsStability
    keywordsStress
    keywordsPartial differential equations
    keywordsOscillations
    keywordsComputer simulation
    keywordsSteady state
    keywordsAlgorithms AND Density
    treeJournal of Applied Mechanics:;2009:;volume( 076 ):;issue: 003
    contenttypeFulltext
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