Structure functions in turbulence, in various flow configurations, at Reynolds number between 30 and 5000, using extended self-similarity

Arnéodo, A.; Baudet, Christophe; Belin, F.; Benzi, Roberto; Castaing, B.; Chabaud, Benoît; Chavarria, R.; Ciliberto, S.; Camussi, Roberto; Chillà, Francesca; Dubrulle, Bérengère; Gagne, Yves; Hébral, B.; Herweijer, JA; Marchand, Michel; Maurer, J.; Muzy, Jean–François; Naert, Antoine; Noullez, A.; Peinke, Joachim; Roux, Filippus S.; Tabeling, Patrick; Water, Willem van de; Willaime, Hervé

doi:10.1209/epl/i1996-00472-2

Cited by 230 publications

(196 citation statements)

References 16 publications

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“…where the parameter µ is called "intermittency parameter" and is close to 0.25 (Arneodo et al, 1996). The function ζ vH (q) obtained from our database is nonlinear and concave similar to the results obtained in previous studies (Schmitt et al, 1993;Schertzer et al, 1997), with the following properties:…”

Section: Scaling Exponent Function ζ Vh For the Inertial Rangesupporting

confidence: 82%

Multiscaling and joint multiscaling description of the atmospheric wind speed and the aggregate power output from a wind farm

Calif¹,

Schmitt²

2014

Nonlin. Processes Geophys.

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Abstract. We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T 10 3 s 15 min.

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Section: Scaling Exponent Function ζ Vh For the Inertial Rangesupporting

confidence: 82%

Multiscaling and joint multiscaling description of the atmospheric wind speed and the aggregate power output from a wind farm

Calif¹,

Schmitt²

2014

Nonlin. Processes Geophys.

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“…39,40 Numerical and experimental observations show that clean scaling behavior for the Eulerian structure functions is found only in a range 10 Յ r L ͑see Ref. 41 for a collection of experimental and numerical results͒. For spatial scales r Ͻ 10 , multiscaling properties, typical of the intermediate dissipative range, are observed due to the superposition of inertial and dissipative range physics.…”

Section: Introductionmentioning

confidence: 97%

Lagrangian structure functions in turbulence: A quantitative comparison between experiment and direct numerical simulation

et al. 2008

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Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers)Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication Citation for published version (APA):Biferale, L., Bodenschatz, E., Cencini, M., Lanotte, A. S., Ouellette, N. T., Toschi, F., & Xu, H. (2008). Lagrangian structure functions in turbulence : a quantitative comparison between experiment and direct numerical simulation. Physics of Fluids, 20(6), 065103-1/12. [065103]. DOI: 10.1063/1.2930672 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. A detailed comparison between data from experimental measurements and numerical simulations of Lagrangian velocity structure functions in turbulence is presented. Experimental data, at Reynolds number ranging from R = 350 to R = 815, are obtained in a swirling water flow between counter-rotating baffled disks. Direct numerical simulations ͑DNS͒ data, up to R = 284, are obtained from a statistically homogeneous and isotropic turbulent flow. By integrating information from experiments and numerics, a quantitative understanding of the velocity scaling properties over a wide range of time scales and Reynolds numbers is achieved. To this purpose, we discuss in detail the importance of statistical errors, anisotropy effects, and finite volume and filter effects, finite trajectory lengths. The local scaling properties of the Lagrangian velocity increments in the two data sets are in good quantitative agreement for all time lags, showing a degree of intermittency that changes if measured close to the Kolmogorov time scales or at larger time lags. This systematic study resolves apparent disagreement between observed experimental and numerical scaling pro...

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“…Anselmet et al 1984;Frisch 1995). To firmly establish the universality of the ISR statistics, the so-called extended self-similarity (ESS) hypothesis of Benzi et al (1993Benzi et al ( , 1995 played a central role (Arneodo et al 1996;Belin et al 1996). In this framework, instead of evaluating the scaling of the structure functions directly as a function of distance, the relative scaling exponent is sought by plotting one structure function against another one of different order on log-log scales.…”

Section: Introductionmentioning

confidence: 99%

Statistics of turbulence in the energy-containing range of Taylor–Couette compared to canonical wall-bounded flows

Krug¹,

Yang²,

Silva³

et al. 2017

J. Fluid Mech.

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Considering structure functions of the streamwise velocity component in a framework akin to the extended self-similarity hypothesis (ESS), de Silva et al. (J. Fluid Mech., vol. 823,2017, pp. 498-510) observed that remarkably the large-scale (energy-containing range) statistics in canonical wall bounded flows exhibit universal behaviour. In the present study, we extend this universality, which was seen to encompass also flows at moderate Reynolds number, to Taylor-Couette flow. In doing so, we find that also the transversal structure function of the spanwise velocity component exhibits the same universal behaviour across all flow types considered. We further demonstrate that these observations are consistent with predictions developed based on an attached-eddy hypothesis. These considerations also yield a possible explanation for the efficacy of the ESS framework by showing that it relaxes the self-similarity assumption for the attached eddy contributions. By taking the effect of streamwise alignment into account, the attached eddy model predicts different behaviour for structure functions in the streamwise and in the spanwise directions and that this effect cancels in the ESS-framework -both consistent with the data. Moreover, it is demonstrated here that also the additive constants, which were previously believed to be flow dependent, are indeed universal at least in turbulent boundary layers and pipe flow where high-Reynolds number data are currently available.

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Structure functions in turbulence, in various flow configurations, at Reynolds number between 30 and 5000, using extended self-similarity

Cited by 230 publications

References 16 publications

Multiscaling and joint multiscaling description of the atmospheric wind speed and the aggregate power output from a wind farm

Multiscaling and joint multiscaling description of the atmospheric wind speed and the aggregate power output from a wind farm

Lagrangian structure functions in turbulence: A quantitative comparison between experiment and direct numerical simulation

Statistics of turbulence in the energy-containing range of Taylor–Couette compared to canonical wall-bounded flows

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