epl draft Autocorrelation function of velocity increments 1 time series in fully developed turbulence
نویسندگان
چکیده
Abstract. In fully developed turbulence, the velocity field possesses long-range correlations, 10 denoted by a scaling power spectrum or structure functions. Here we consider the autocorrelation 11 function of velocity increment Δu`(t) at separation distance time `. Anselmet et al. [Anselmet 12 et al. J. Fluid Mech. 140, 63 (1984)] have found that the autocorrelation function of velocity 13 increment has a minimum value, whose location is approximately equal to `. Taking statistical 14 stationary assumption, we link the velocity increment and the autocorrelation function with the 15 power spectrum of the original variable. We then propose an analytical model of the autocorrelation 16 function. With this model, we prove that the location of the minimum autocorrelation function is 17 exactly equal to the separation scale time ` when the scaling of the power spectrum of the original 18 variable belongs to the range 0 < β < 2. This model also suggests a power law expression for the 19 minimum autocorrelation. Considering the cumulative function of the autocorrelation function, it 20 is shown that the main contribution to the autocorrelation function comes from the large scale part. 21 Finally we argue that the autocorrelation function is a better indicator of the inertial range than 22 the second order structure function. 23
منابع مشابه
Parametric study of a viscoelastic RANS turbulence model in the fully developed channel flow
One of the newest of viscoelastic RANS turbulence models for drag reducing channel flow with polymer additives is studied in different flow and rheological properties. In this model, finitely extensible nonlinear elastic-Peterlin (FENE-P) constitutive model is used to describe the viscoelastic effect of polymer solution and turbulence model is developed in the k-ϵ-(ν^2 ) ̅-f framework. The geome...
متن کاملRevealing intermittency in experimental data with steep power spectra
The statistics of signal increments are commonly used in order to test for possible intermittent properties in experimental or synthetic data. However, for signals with steep power spectra [i.e., E(ω) ∼ ω−n with n ≥ 3], the increments are poorly informative and the classical phenomenological relationship between the scaling exponents of the second-order structure function and of the power spect...
متن کاملRainfall-runoff process modeling using time series transfer function
Extended Abstract 1- Introduction Nowadays, forecasting and modeling the rainfall-runoff process is essential for planning and managing water resources. Rainfall-Runoff hydrologic models provide simplified characterizations of the real-world system. A wide range of rainfall-runoff models is currently used by researchers and experts. These models are mainly developed and applied for simulation...
متن کاملLagrangian covariance analysis of homogeneous -plane turbulence
J. R. Ristorcelli X Division, Los Alamos National Laboratory University of California, Los Alamos, NM 87545 A.C. Poje Division of Applied Mathematics Brown University, Providence, RI 02192 Abstract The e ects of Rossby wave { turbulence interactions on particle dispersion are investigated in a Lagrangian analysis of the potential vorticity equation. The analysis produces several exact statistic...
متن کاملMagnetohydrodynamic turbulence: Observation and experiment
We provide a tutorial on the paradigms and tools of magnetohydrodynamic (MHD) turbulence. The principal paradigm is that of a turbulent cascade from large scales to small, resulting in power law behavior for the frequency power spectrum for magnetic fluctuations EBðf Þ. We will describe five useful statistical tools for MHD turbulence in the time domain: the temporal autocorrelation function, t...
متن کامل