Detecting vorticity filaments using wavelet analysis: About the statistical contribution of vorticity filaments to intermittency in swirling turbulent flows

Swirling turbulent flows display intermittent pressure drops associated wit h intense vorticity filaments. Using the wavelet transform modulus maxima r epresentation of pressure fluctuations, we propose a method of characterizi ng these pressure drop events from their time-scale properties. This method allows us to discriminate fluctuations induced by just formed (young) as w ell as by burst (old) filaments from background pressure fluctuations. The statistical characteristics of these filaments (core size, waiting time) ar e analyzed in details and compared with previously reported experimental an d 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 press ure 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 no t important enough to account for the intermittency phenomenon in turbulent s flows.