Uncertainty quantification for velocity measurement with 2D2C particle image velocimetry

Abstract

Abstract In this paper, a theoretical model of dimensionless instantaneous and average velocity measurement uncertainty quantification with 2D2C particle image velocimetry (PIV) is established under the framework of generally adopted international uncertainty quantification standards. The effectiveness of the model is verified using uniform flow field testing data. Combined with semi-quantitative analysis of the theoretical model, uncertainty control suggestions for PIV measurements are given. The major sources affecting the uncertainty of instantaneous velocity measurements are the reference velocity, particle instantaneous pixel displacement, and their correlation term. For average velocity measurement uncertainty quantification, the uncertainty of particle average pixel displacement is effectively controlled by taking a large number of particle images. Thus, three single-component terms — the calibration factor, particle average pixel displacement and reference velocity — and two correlation terms — the particle average pixel displacement–calibration factor and the particle average pixel displacement–reference velocity — all make an important contribution to the average velocity measurement uncertainty. To reduce the uncertainty of PIV velocity measurement, one can reduce the reference velocity measurement uncertainty, optimize the PIV algorithm and improve the calibration factor by applying a high spatial resolution imaging system in experiments. In addition, reducing the reference velocity measurement uncertainty and improving the spatial resolution are key feasible methods.