Advances in PIV Uncertainty Quantification

Abstract

Particle Image Velocimetry (PIV) is a leading technique that allows flow velocity measurements in two- and three- dimensional domains. PIV is a full-field, non-intrusive and quantitative technique. However, due to the complexity of the measurement chain, PIV results are often affected by errors from various sources. It is therefore necessary to identify these errors and quantify the uncertainties. The available PIV uncertainty quantification (UQ) approaches are limited in estimating systematic uncertainties in the measurements and mostly focus on the random uncertainty. In order to exploit full benefits of PIV, the knowledge of the full uncertainty comprising both random and systematic uncertainties is necessary. The present work proposes a comprehensive PIV-UQ framework which not only quantifies the systematic uncertainties but is also universal as it can potentially be used for any measurement irrespective of the measurement setup (e.g. planar PIV, tomographic PTV, large scale PIV or microscopic PTV) or the output quantity (e.g. mean velocity or higher order statistics).