Statistics of 3-dimensional Lagrangian turbulence
arXiv:cond-mat/0606655 · doi:10.1103/PhysRevLett.98.064502
Abstract
We consider a superstatistical dynamical model for the 3-d movement of a Lagrangian tracer particle embedded in a high-Reynolds number turbulent flow. The analytical model predictions are in excellent agreement with recent experimental data for flow between counter-rotating disks. In particular, we calculate the Lagrangian scaling exponents zeta_j for our system, and show that they agree well with the measured exponents reported in [X. Hu et al., PRL 96, 114503 (2006)]. Moreover, the model correctly predicts the shape of velocity difference and acceleration probability densities, the fast decay of component correlation functions and the slow decay of the modulus, as well as the statistical dependence between acceleration components. Finally, the model explains the numerically [P.K. Yeung and S.B. Pope, J. Fluid Mech. 207, 531 (1989)] and experimentally observed fact [B.W. Zeff et al., Nature 421, 146 (2003)] that enstrophy lags behind dissipation.
5 pages, 3 figures. Replaced by final version accepted by Phys. Rev. Lett
References in corpus (3)
Cited by in corpus (24)
- Superstatistics, thermodynamics, and fluctuations
- Lagrangian Structure Functions in Turbulence: A Quantitative Comparison between Experiment and Direct Numerical Simulation
- Superstatistics in high energy physics: Application to cosmic ray energy spectra and e+e- annihilation
- Superstatistical distributions from a maximum entropy principle
- Kinetic theory of two dimensional point vortices from a BBGKY-like hierarchy
- Lagrangian structure functions in fully-developed hydrodynamical turbulence
- Variation of fundamental constants in space and time: theory and observations
- Statistics of Lagrangian quantum turbulence
- On superstatistical multiplicative-noise processes
- Scaling of acceleration statistics in high Reynolds number turbulence
- Analyzing Spatio-Temporal Dynamics of Dissolved Oxygen for the River Thames using Superstatistical Methods and Machine Learning
- Superstatistical analysis of sealevel fluctuations
- Multicanonical distribution: Statistical equilibrium of multiscale systems
- Power-law statistics in the velocity fluctuations of Brownian particle in inhomogeneous media and driven by colored noise
- Statistical mixing and aggregation in Feller diffusion
- Multi-time structure functions and the Lagrangian scaling of turbulence
- Lagrangian quantum turbulence model based on alternating superfluid/ normal fluid stochastic dynamics
- Extreme Value Laws for Superstatistics
- On discrete stochastic processes with long-lasting time dependence
- Superstatistical wind fields from point-wise atmospheric turbulence measurements
- First passage time for superstatistical Fokker-Planck models
- Spatial analysis of tails of air pollution PDFs in Europe
- Minding impacting events in a model of stochastic variance
- Skewed superstatistical distributions from a Langevin and Fokker-Planck approach