An amplitude-frequency study of turbulent scaling intermittency using Empirical Mode Decomposition and Hilbert Spectral Analysis
By Y. X. Huang, F. G. Schmitt, Z. M. Lu, Y. Liu. 2008
156 citations recorded by the source corpus.
Hilbert-Huang transform is a method that has been introduced recently to decompose nonlinear, nonstationary time series into a sum of different modes, each one having a characteristic frequency. Here we show the first successful application of this approach to homogeneous turbulence time series. We associate each mode to dissipation, inertial range and integral scales. We then generalize this approach in order to characterize the scaling intermittency of turbulence in the inertial range, in an amplitude-frequency space. The new method is first validated using fractional Brownian motion simulations. We then obtain a 2D amplitude-frequency representation of the pdf of turbulent fluctuations with a scaling trend, and we show how multifractal exponents can be retrieved using this approach. We also find that the log-Poisson distribution fits the velocity amplitude pdf better than the lognormal distribution.
Subfields: Economics and Econometrics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/59266c826e1c550d272e676705df2aa0f34fa855
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Citations in the corpus
- Analysis of daily river flow fluctuations using Empirical Mode Decomposition and arbitrary order Hilbert spectral analysis (2009, methodology): “…(Su et al., 2008),154 geophysics (Jánosi and Müller, 2005), climate studies (Solé et al., 2007), me-155 chanical engineering (Chen et al., 2004), acoustics (Loutridis, 2005), aquatic156 environment (Schmitt et al., 2007, 2008) and turbulence (Huang et al., 2008),157 to quote a few.158 2.3.”