The subject of this paper is a statistical method for the accurate evaluation of the uncertainties for pneumatic multi-hole probe measurements. The method can be applied to different types of evaluation algorithms and is suitable for steady flowfield measurements in compressible flows. The evaluation of uncertainties is performed by a Monte Carlo method (MCM), which is based on the statistical law of large numbers. Each input quantity, including calibration and measurement quantities, is randomly varied on the basis of its corresponding probability density function (PDF) and propagated through the deterministic parameter evaluation algorithm. Other than linear Taylor series based uncertainty evaluation methods, MCM features several advantages. On the one hand, MCM does not suffer from lower-order expansion errors and can therefore reproduce nonlinearity effects. On the other hand, different types of PDFs can be assumed for the input quantities and the corresponding coverage intervals can be calculated for any coverage probability.

To demonstrate the uncertainty evaluation, a calibration and subsequent measurements in the wake of an airfoil with a 5-hole probe are performed. MCM is applied to different parameter evaluation algorithms. It is found that the MCM approach presented cannot be applied to polynomial curve fits, if the differences between the calibration data and the polynomial curve fits are of the same order of magnitude compared to the calibration uncertainty.

Since this method has not yet been used for the evaluation of measurement uncertainties for pneumatic multi-hole probes, the aim of the paper is to present a highly accurate and easy-to-implement uncertainty evaluation method.

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