https://doi.org/10.1007/s100510050694
Detecting vorticity filaments using wavelet analysis: About the statistical contribution of vorticity filaments to intermittency in swirling turbulent flows
1
NASA's Goddard Space Flight Center,
Climate and Radiation Branch (code 913), Greenbelt, MD 20771, USA
2
Centre de Recherches Mathématiques, Université de Montréal, C.P. 6128,
Succ. Centre-ville, H3C 3J7 Montréal (Quebec), Canada
3
Centre de Recherche Paul Pascal, Avenue Schweitzer, 33600 Pessac, France
Received:
27
July
1998
Revised:
23
November
1998
Published online: 15 March 1999
Swirling turbulent flows display intermittent pressure drops associated with intense vorticity filaments. Using the wavelet transform modulus maxima representation of pressure fluctuations, we propose a method of characterizing these pressure drop events from their time-scale properties. This method allows us to discriminate fluctuations induced by just formed (young) as well as by burst (old) filaments from background pressure fluctuations. The statistical characteristics of these filaments (core size, waiting time) are analyzed in details and compared with previously reported experimental and numerical findings. Their intermittent occurrence is found to be governed by a pure Poisson's law, the hallmark of independent events. Then we apply the wavelet transform modulus maxima (WTMM) method to the background pressure fluctuations. This study reveals that, once removed all the filaments, the "multifractal" nature of pressure fluctuations still persists. This is a clear indication that the statistical contribution of the filaments is not important enough to account for the intermittency phenomenon in turbulents flows.
PACS: 02.50.-r – Probability theory, stochastic processes, and statistics / 05.40.+j – Fluctuation phenomena, random processes, and Brownian motion / 47.27.Gs – Isotropic turbulence; homogeneous turbulence / 47.32.-y – Rotational flow and vorticity
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 1999