Abstract

The boundary layer transition induced by distributed surface roughness has great practical relevance, but remains poorly understood. In this experimental work, we investigate the transition in a flat-plate boundary layer downstream of a localized strip of random distributed roughness. The boundary layer exhibits different temporal and spectral behaviour in two (roughness-) Reynolds-number regimes separated by a critical value. In the “sub-critical” regime, the velocity signals show presence of “turbulent spots”, whereas in the “super-critical” regime, no distinct turbulent spots are observed. Two boundary-layer profiles, one each from the sub-critical and super-critical regimes, are chosen for comparison. The sub-critical case exhibits a bi-modal power spectrum having two humps in frequency ranges differing by an order of magnitude, whereas the super-critical case has a uni-modal spectrum with a single hump in the high-frequency range. The wavelet analysis shows that the energy distribution is intermittent in time for both the cases at all frequencies. However, for the sub-critical case, the energy in the high-frequency range appears as clusters, which are seen as turbulent spots in the velocity signal. On the other hand, for the super-critical case there is no such clustering, consistent with the absence of spots in the velocity signal. We conjecture that, for the sub-critical case, the motions corresponding to the low-frequency spectral hump (possibly the streamwise streaks) could be responsible for imparting organization to the high-frequency motions in the form of turbulent spots. We also detect “events” in the wavelet-energy time series. For the sub-critical case, the events in the high-frequency range have a higher degree of time-localization, which increases with frequency. For the super-critical case, however, the time-localization is independent of frequency over nearly the entire frequency range. These findings present two different scenarios for the late stages of transition, having distinct time-frequency behaviour. This could have implications towards modelling roughness-induced transition.

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