ASSESSMENT OF TURBULENT SPECTRAL BIAS IN LASER-DOPPLER VELOCIMETRY

Abstract

A critical evaluation is made of the spectral bias which occurs in the use of a laser Doppler velocimeter (LDV). In order to accommodate the randomly sampled LDV data, statistical treatments of particle arrival times are needed. This is modeled as a doubly stochastic Poisson process which includes the intensity function of the velocity field. Three processing algorithms are considered for spectral estimates: the sample and hold method (SH), the modified Shannon sampling technique (SR), and the direct transform (RG). Assessment is made of these for varying data densities (0.05 less-than-or-equal-to d.d less-than-or-equal-to 5) and turbulence levels (t.i. = 30%, 100%). The effects of the values of the Reynolds stress coefficients and the transversal standard deviation on the spectral contents were examined. As an improved version of the spectral estimator, the utility of POCS (the projection onto convex sets) has been tested in the present study. This algorithm is found useful to be in the region when d.d. less-than-or-similar-to 3.