Assessment of LDV spectral bias based on three-dimensional velocity fields

Abstract

An extensive evaluation is made of the spectral bias in the use of a burst-type laser Doppler velocimeter (LDV). An improved version of the autoregressive vector model (ARV) to handle the full three-dimensional velocity fields is proposed. The particle arrival time statistics are modeled as a doubly stochastic Poisson process. Four well-known spectral algorithms, i.e., the direct transform method (RG), the transit time-weighting method (TW), the sample and holds interpolation method (SH), and the nonuniform Shannon reconstruction technique (SR), are evaluated and compared with the theoretical spectra for various sampling and flow conditions. Assessment is made of these processing algorithms over a broad range of data densities (0.05 ≤ d.d. ≤ 5.0) and turbulence levels (t.i. = 0.3, 1.0). In order to move closer to realistic experimental conditions, the influences of the ratio of the minimum number of periods required for frequency estimation to the maximum fringe number of the measuring volume (Q = 0.57), and the relative velocity by frequency shifting (R = 5.0) on spectral distortion are examined. Furthermore, the effect of the Reynolds stress coefficients on spectral bias is scrutinized. © 1997 Elsevier Science Ltd.