A new signal decomposition technique was applied to analyze the hot-wire signal in the unsteady turbulent wake of an airfoil, in which the instantaneous velocity is characterized by the sum of the large-scale motion due to vortex shedding and the random turbulent motion. The techanique uses power spectrum of data to deduce the optimal frequency-domain filter to determine the periodic and turbulent components of a time series of data. The contribution of all turbulent eddies of the random component are estimated with an adaptive turbulence filter, which recognizes this component as the orthogonal partner to periodic motion, with a power spectrum of appropriate shape. The method is significantly more general than the phase average in its applicability and makes more efficient use of available data.
Measurement was focused on the near wake. Turbulence data including the Reynolds stress distribution was obtained to characterize the flow.
