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The development of a novel slotting technique for the estimation of the autocorrelation function (ACF) of randomly sampled data has eliminated the major disadvantages of the Mayo algorithm. The reduced variance of the estimators in the vicinity of τ = 0 and the elimination of estimators greater than 1 has opened the possibility to approximate the ACF with a curve-fit, leading to a noise-free estimator of the power spectrum. In this paper we describe an analytical function, based on known properties of turbulence power spectra, which is suited to the approximation of the ACF from randomly sampled laser-Doppler anemometry (LDA) data with noise. Using simulated LDA data, based on both simulated and hot-wire measured turbulence signals, it is shown that the method estimates the power spectrum with an error of less than 25% over six decades of power. Application to various LDA data sets shows that the analytical function, derived from the spectral properties, is sufficiently flexible to describe ACFs from data sets of pipe flow, mixing layer flow, flow in stirred tanks and flows around airfoils. An extension of the technique could be in automatic incorporation of periodic components and compensation for data sets with a high velocity bias (turbulence intensities > 40%).

The estimation of turbulence power spectra from randomly sampled laser Doppler anemometer (LDA) data can be done via the autocorrelation function (ACF) approach, whereby the slotting technique has the advantage that the ACF can be estimated at any data rate. Two improvements on Mayo's slotting technique for estimating the ACF, `local normalization' and the `fuzzy slotting technique', were proposed and compared in a benchmark test. However, it proved possible to merge these approaches and the resulting algorithm produced correlation coefficients with a lower variance than either of the individual algorithms. This lower variance in the ACF estimates can then be capitalized upon in order to produce better estimates of the turbulence power spectrum.

A theoretical model for gas ᎐ liquid annularrdispersed flow through a ®enturi meter is reported. It is based on an earlier model de®eloped for ®enturi scrubbers. Changes implemented are based on new research and on the different physics between the two cases. The predictions of the model ha®e been tested using information from recent experiments on ®enturi meters employed for measuring wet-gas flows with a liquid ®ol-ume fraction up to 10%. The model gi®es good predictions with appropriate ®alues of a small set of input ®ariables.