Literature DB >> 21599307

Different methods to estimate the Einstein-Markov coherence length in turbulence.

R Stresing1, D Kleinhans, R Friedrich, J Peinke.   

Abstract

We study the Markov property of experimental velocity data of different homogeneous isotropic turbulent flows. In particular, we examine the stochastic "cascade" process of nested velocity increments ξ(r):=u(x+r)-u(x) as a function of scale r for different nesting structures. It was found in previous work that, for a certain nesting structure, the stochastic process of ξ(r) has the Markov property for step sizes larger than the so-called Einstein-Markov coherence length l(EM), which is of the order of magnitude of the Taylor microscale λ [Phys. Lett. A 359, 335 (2006)]. We now show that, if a reasonable definition of the effective step size of the process is applied, this result holds independently of the nesting structure. Furthermore, we analyze the stochastic process of the velocity u as a function of the spatial position x. Although this process does not have the exact Markov property, a characteristic length scale l(u(x))≈l(EM) can be identified on the basis of a statistical test for the Markov property. Using a method based on the matrix of transition probabilities, we examine the significance of the non-Markovian character of the velocity u(x) for the statistical properties of turbulence.

Year:  2011        PMID: 21599307     DOI: 10.1103/PhysRevE.83.046319

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  1 in total

1.  Quantifying memory in complex physiological time-series.

Authors:  Amir H Shirazi; Mohammad R Raoufy; Haleh Ebadi; Michele De Rui; Sami Schiff; Roham Mazloom; Sohrab Hajizadeh; Shahriar Gharibzadeh; Ahmad R Dehpour; Piero Amodio; G Reza Jafari; Sara Montagnese; Ali R Mani
Journal:  PLoS One       Date:  2013-09-05       Impact factor: 3.240

  1 in total

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