Spectral structure and linear mechanisms in a rapidly distorted boundary layer

The aim of the present work is to investigate the spectral structure of a rapidly distorted boundary layer that develops on a flat plate in presence of a localised patch of roughness or/and grid-generated freestream turbulence. We observe that, at a certain distance downstream of the roughness patch the boundary layer exhibits a bimodal shape in the energy spectrum of the streamwise velocity fluctuations, similar to that found in a fully-turbulent boundary layer at relatively high Reynolds numbers. The physical mechanism that gives rise to the low-wavenumber peak in the spectrum, which represents long stream wise motions or superstructures, is identified to be the interaction of the broadband disturbances with the region of high shear near the wall in the boundary layer. We next show that the flat-plate boundary layer combined with surface roughness and grid turbulence can serve as building-block elements towards synthesising the wall-normal structure of a canonical turbulent boundary layer, in the context of large-scale streamwise motions. The rapidly distorted (or synthetic) boundary layer presents a simpler environment in which the coherent motions can evolve and therefore can enable a better characterisation of these motions. To further illustrate the utility of the present approach we compare results from our measurements with the predictions of the Rapid Distortion Theory (RDT). We show that the stream wise turbulence energy in the near-wall region of the rapidly distorted boundary layer grows linearly with time consistent with the RDT results on the effect of pure shear on an initially isotropic turbulence. Moreover close to the edge of the boundary layer the large-scale fluctuations experience an enhancement in the streamwise turbulence energy in accordance with the linear blocking model in the RDT framework. The present work thus highlights the importance of linear processes in wall turbulence and can help us identify aspects of it to which the linear theories can be meaningfully applied. (c) 2017 The Authors. Published by Elsevier Inc.