A multi-wavelet frequency sift analysis method for analyzing intermittency in transitional flow

Transition to turbulence is marked by intermittent flow structures, commonly referred to as "turbulent puffs", and causes fluctuations in flow parameters. Quantifying this fluctuating, intermittent flow behavior is important as it can accelerate material failure and cause performance reductions in flow-systems. 'Intermittency' inherently suggests that the flow structures maintain a characteristic time-scale, such that time-frequency-based methods can be effective for such analysis. However, existing time-frequency-based analysis tools, such as the empirical mode decomposition (EMD), have been noted to fail for intermittent signals, as observed in transitional flows. In this work, we propose a novel method that utilizes the dual-tree continuous wavelet transform (DT-CWT) and a frequency isolation sifting process in order to evaluate the instantaneous frequencies of a flow field. We demonstrate our method using particle image velocimetry (PIV) data of transitional pulsatile pipe flow. Furthermore, we compare this flow frequency information to traditional analysis such as coherent structure identification to demonstrate its utility in analyzing transitional flows.