2015
DOI: 10.1063/1.4907740
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Gradual wavelet reconstruction of the velocity increments for turbulent wakes

Abstract: This work explores the properties of the velocity increment distributions for wakes of contrasting local Reynolds number and nature of generation (a cylinder wake and a multiscale-forced case, respectively). It makes use of a technique called gradual wavelet reconstruction (GWR) to generate constrained randomizations of the original data, the nature of which is a function of a parameter, ϑ. This controls the proportion of the energy between the Markov-Einstein length (∼ 0.8 Taylor scales) and integral scale th… Show more

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Cited by 15 publications
(9 citation statements)
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References 74 publications
(112 reference statements)
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“…More recently, Hosokawa [52] showed a dependence between velocity increments and the local velocity sum that was broadly consistent with the conclusion of Praskovsky et al [51]. Further work on velocity dependence can be seen in studies that move away from considering the velocity increment moments (structure functions) to studying a Fokker-Planck equation for the evolution of the probability density function of the increments [53,54]. By further conditioning the distribution for p(∆u r |∆u 2r ) on the velocity, i.e.…”
Section: Velocity-intermittency Analysissupporting
confidence: 64%
“…More recently, Hosokawa [52] showed a dependence between velocity increments and the local velocity sum that was broadly consistent with the conclusion of Praskovsky et al [51]. Further work on velocity dependence can be seen in studies that move away from considering the velocity increment moments (structure functions) to studying a Fokker-Planck equation for the evolution of the probability density function of the increments [53,54]. By further conditioning the distribution for p(∆u r |∆u 2r ) on the velocity, i.e.…”
Section: Velocity-intermittency Analysissupporting
confidence: 64%
“…Based on multi-scale statistics, found that fractal grid generated turbulence exhibits different scaling features and multi-scale statistics than commonly generated flows (cylinder wake and free jet), defining a novel class of turbulence. The work of ; Keylock et al (2015) gives first indications that the turbulent cascade and its Kramers-Moyal coefficients depend on the turbulence generation mechanism. This dependence on turbulence generation contrasts with the universal features found on the basis of 2-point statistics involving structure functions and its scaling exponents.…”
Section: Introductionmentioning
confidence: 99%
“…Given that the ρ = 0 surrogates in GWR remove multifractal characteristics, this formulation is very useful for studying the properties of multifractal signals as a function of ρ. For example, an analysis of the velocity increments in turbulence highlighted the importance of two (from four) parameters in a Fokker-Planck model for these increments for the nonlinear structure of turbulence [36]. Gradual wavelet reconstruction showed both that these terms, which are an order of magnitude smaller than the other two terms, are signicantly diferent to zero in turbulent lows and that they are crucial for controlling the multifractal behaviour.…”
Section: Introductionmentioning
confidence: 99%