Identification and control of Taylor-Gortler vortices in turbulent curved channel flow

Abstract

Direct numerical simulations of turbulent flows in a curved channel are performed. The drifting Taylor-Gortler vortices are identified by applying a conditional averaging. A new algorithm is proposed for identifying the drifting Taylor-Gortler vortices based on the wavelet transform of wall information. A continuous wavelet transform with Marr wavelets is employed to decompose the flow signals at a chosen length scale. An active cancellation is applied to attenuate the Taylor-Gortler vortices and to reduce the wall skin friction.