Effects of vortex filaments on the velocity of tracers and heavy particles in turbulence

Bec, Jérémie; Biferale, Luca; Cencini, Massimo; Lanotte, Alessandra S.; Toschi, Federico

doi:10.1063/1.2338598

Cited by 38 publications

(30 citation statements)

References 31 publications

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“…23 This fact has been supported by DNS investigations of inertial particles. 14,17,29 The agreement between the DNS and the experimental data in this range is remarkable. For p =6 ͓Fig.…”

Section: Phys Fluids 20 065103 ͑2008͒supporting

confidence: 55%

“…DNS data, obtained at lower Reynolds number, allowed simultaneous measurements in both of these ranges. 23,29 For 10 Յ Յ 50 , scaling exponents were found to be slightly less intermittent than those measured with the acoustic techniques, although again compatible within error bars. On the other hand, DNS data 29,33,42 for small time lags, 2 Յ Յ 6 , agree with scaling exponents measured in Ref.…”

Section: Introductionsupporting

confidence: 49%

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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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“…23 This fact has been supported by DNS investigations of inertial particles. 14,17,29 The agreement between the DNS and the experimental data in this range is remarkable. For p =6 ͓Fig.…”

Section: Phys Fluids 20 065103 ͑2008͒supporting

confidence: 55%

Section: Introductionsupporting

confidence: 49%

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

et al. 2008

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“…The first one, originally proposed in [6], is preferential concentration of heavy (light) particles in the strain (vortical) regions of the flow. This effect has been recently observed also in the case of particles with very small inertia [22,23]. The second mechanism, already present in one dimension (1D) [21,24], is that of the particles catching one another in their motion, as they slip with respect to the fluid.…”

Section: Introductionmentioning

confidence: 93%

Concentration fluctuations of large Stokes number particles in a one-dimensional random velocity field

Olla

Vuolo

2007

Phys. Rev. E

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We analyze the behavior of an ensemble of inertial particles in a one-dimensional smooth Gaussian velocity field, in the limit of large inertia, but considering a finite correlation time for the random field. The amplitude of the concentration fluctuations is characterized by slow decay at large inertia and a much larger correlation length than that of the random field. The fluctuation structure in velocity space is very different from predictions from short-time correlated random velocity fields, with only few particle pairs crossing at sufficiently small relative velocity to produce correlations. Concentration fluctuations are associated with depletion of the relative velocity variance of colliding particles.

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“…Particles of this type are commonly used for flow visualization in fluid mechanics experiments [39]. We remark that the complete equation for the motion of a material particle in a fluid when density and volume effects are taken into account can be rather complicated [40,41]. The Lagrangian equation of motion (40) formally represents a dynamical system in the phase space of physical coordinates.…”

Section: The Relation Between Eulerian and Lagrangian Statisticsmentioning

confidence: 99%

Twenty-five years of multifractals in fully developed turbulence: a tribute to Giovanni Paladin

Boffetta¹,

Mazzino²,

Vulpiani³

2008

J. Phys. A: Math. Theor.

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The paper On the multifractal nature of fully developed turbulence and chaotic systems, by R. Benzi et al. published in this journal in 1984 ( vol 17, page 3521) has been a starting point of many investigations on the different faces of selfsimilarity and intermittency in turbulent phenomena. Since then, the multifractal model has become a useful tool for the study of small scale turbulence, in particular for detailed predictions of different Eulerian and Lagrangian statistical properties. In the occasion of the 50-th birthday of our unforgettable friend and colleague Giovanni Paladin , we review here the basic concepts and some applications of the multifractal model for turbulence.

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Effects of vortex filaments on the velocity of tracers and heavy particles in turbulence

Abstract: Physics of Fluids, 18, p. 1702, http://dx.doi.org./10.1063/1.2338598International audienc

Cited by 38 publications

References 31 publications

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

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

Concentration fluctuations of large Stokes number particles in a one-dimensional random velocity field

Twenty-five years of multifractals in fully developed turbulence: a tribute to Giovanni Paladin

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