Statistics of single and multiple floaters in experiments of surface wave turbulence

Grosso, Nicolás F. Del; Cappelletti, L.; Sujovolsky, Nicolás Eduardo; Mininni, Pablo D.; Cobelli, Pablo

doi:10.1103/physrevfluids.4.074805

Cited by 8 publications

(6 citation statements)

References 53 publications

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“…Beyond the above Eulerian specifications of the wave field, recent articles report the use of particle tracking velocimetry of Lagrangian buoyant particles or floaters to study gravity-capillary wave turbulence (Del Grosso et al 2019, Cabrera & Cobelli 2021).…”

Section: Single-point Measurementsmentioning

confidence: 99%

Experiments in Surface Gravity–Capillary Wave Turbulence

Falcon

Mordant

2022

Annu. Rev. Fluid Mech.

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The last decade has seen a significant increase in the number of studies devoted to wave turbulence. Many deal with water waves, as modeling of ocean waves has historically motivated the development of weak turbulence theory, which addresses the dynamics of a random ensemble of weakly nonlinear waves in interaction. Recent advances in experiments have shown that this theoretical picture is too idealized to capture experimental observations. While gravity dominates much of the oceanic spectrum, waves observed in the laboratory are in fact gravity–capillary waves, due to the restricted size of wave basins. This richer physics induces many interleaved physical effects far beyond the theoretical framework, notably in the vicinity of the gravity–capillary crossover. These include dissipation, finite–system size effects, and finite nonlinearity effects. Simultaneous space-and-time-resolved techniques, now available, open the way for a much more advanced analysis of these effects. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 54 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Section: Single-point Measurementsmentioning

confidence: 99%

Experiments in Surface Gravity–Capillary Wave Turbulence

Falcon

Mordant

2022

Annu. Rev. Fluid Mech.

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“…Literature on these topics provides examples of different approaches for the study of turbulence. Namely, through experimental setups 3 , 17 , observational data 10 , 11 , particle 18 , fluid 19 , and Vlasov simulations 20 of turbulent plasma systems, Langevin equations 21 , 22 , kinetic equations for weak turbulence 23 , kinetic equations for strong turbulence 24 , chaotic systems 25 , 26 , Shell Models 27 , 28 and Coupled Map Lattices (CML) 25 , 29 .…”

Section: Introductionmentioning

confidence: 99%

Langevin based turbulence model and its relationship with Kappa distributions

Gallo-Méndez

Moya

2022

Sci Rep

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Kappa distributions (or $$\kappa $$ κ -like distributions) represent a robust framework to characterize and understand complex phenomena with high degrees of freedom, as turbulent systems, using non-extensive statistical mechanics. Here we consider a coupled map lattice Langevin based model to analyze the relation of a turbulent flow, with its spatial scale dynamic, and $$\kappa $$ κ -like distributions. We generate the steady-state velocity distribution of the fluid at each scale, and show that the generated distributions are well fitted by $$\kappa $$ κ -like distributions. We observe a robust relation between the $$\kappa $$ κ parameter, the scale, and the Reynolds number of the system, Re. In particular, our results show that there is a closed scaling relation between the level of turbulence and the $$\kappa $$ κ parameter; namely $$\kappa \sim \text {Re}\,k^{-5/3}$$ κ ∼ Re k - 5 / 3 . We expect these results to be useful to characterize turbulence in different contexts, and our numerical predictions to be tested by observations and experimental setups.

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“…The modeling of such flows requires a wide variety of approximations, and their study in the laboratory has important consequences for flow characterization as well for practical applications. Examples of such applications include cloud dynamics and droplet formation [4], aerosol and pollution dispersion in the atmosphere [5], and nutrient transport in the oceans [6] among others [7]. In many cases, the study of particle-laden flows has focused on the paradigmatic case of isotropic and homogeneous turbulence, a landmark in the study of turbulence.…”

Section: Introductionmentioning

confidence: 99%

Velocity and acceleration statistics in particle-laden turbulent swirling flows

2020

Self Cite

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We present a comparison of different particles' velocity and acceleration statistics in two paradigmatic turbulent swirling flows: the von Kármán flow in a laboratory experiment, and the Taylor-Green flow in direct numerical simulations. Tracers, as well as inertial particles, are considered. Results indicate that, in spite of the differences in boundary conditions and forcing mechanisms, scaling properties and statistical quantities reveal similarities between both flows, pointing to new methods to calibrate and compare models for particles dynamics in numerical simulations, as well as to characterize the dynamics of particles in simulations and experiments. The comparison also allows us to identify contributions of the mean flow to the inertial range scaling of the particles' velocity structure functions.

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Statistics of single and multiple floaters in experiments of surface wave turbulence

Cited by 8 publications

References 53 publications

Experiments in Surface Gravity–Capillary Wave Turbulence

Experiments in Surface Gravity–Capillary Wave Turbulence

Langevin based turbulence model and its relationship with Kappa distributions

Velocity and acceleration statistics in particle-laden turbulent swirling flows

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