Abstract:
The streamwise velocity component in the wall turbulentboundary layer disturbed by blowing and suction was measured with hotwire anemometer. FFT transform and wavelet transform were adopted tostudy the effect on the turbulent energy spectrum. The results showthat the disturbance in low frequency makes the turbulent kinetic energy betransferred newly among different turbulent structures. One of theimpact is that the energy of large scale turbulent structures in innerboundary layer obviously decreases, especially in wavelet scale $j=-10$, whichcorresponds to coherent structures. The other effect shows that the energyof small scale turbulent structures increases synchronously near the wall. When themeasured position is leaving from the boundary layer, not only the energyof small structures keeps growing up but also the trend of increased energygradually extends to larger scale structures until the change adds up to themaximum in the borderline between inner and outer ($y_{v}=0.1$) boundarylayers. According to the above-mentioned facts, one may assumethat the large scale turbulent structures are broken up into many smallscale structures arising from the effect of low frequent blowing andsuction. Note that above the boundary layer at $y_{v}=0.15$(the outerboundary layer), the turbulent spectrum graphs with and without disturbanceare identical superposition, which reveals that the influence of blowing andsuction far from the wall boundary layer decays gradually until it disappearsin the outer boundary layer.Furthermore, by means of VITA method and wavelet transform to identify burstevents, it is clear that the disturbance not only reduces the burst intensityand delays the averaged burst period but also diminishes the scope ofconditionally averaged velocity signals and shortens the duration time,which indicates that the disturbance apparently restrains the burst processof coherent structures. Based upon the above described analysis, thedisturbance of blowing and suction is perfectly suited to controll theturbulent flow.In summary, the two methods, wavelet transform and FFT transform, canboth be regarded as perfect tools to analyze the turbulent energy spectrum.Compared with FFT, wavelet transform makes the energy spectrum graph muchsmooth due to its filter function. Another advantage is that itdecomposes theturbulent flow into different frequencies (or scales) which represent multiscales of turbulent structures including coherent structures and dissipativestructures in order to recognize their respective characteristics. Withfree parameters, wavelet transform is not only anobjective and effective utility to identify coherent structures and burstevents but also an important tool to validate and supplement theanalysis of the wall turbulent flow with VITA method.
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