Stereo PIV uncertainty estimation using the Correlation Statistics method


Particle Image Velocimetry is nowadays a widely used non-intrusive measurement method that allows very accurate velocity fields of a flow to be recorded. In order to obtain meaningful results from experiments, it is essential to quantify the uncertainties that occur. Correlation statistics can be used to determine the uncertainty of the PIV algorithm, which is a major challenge.

ITS already has an in-house code for uncertainty quantification, which is to be further developed in this thesis. The developed code is to be validated using synthetic data and compared with commercial systems. Subsequently, the code will be applied to real stereo PIV data and the uncertainty of the experiments will be determined.

The work consists of the following work packages:

  • Familiarization with the topics of PIV and uncertainty estimation using correlation statistics
  • Implementation and validation of the correlation statistics
  • Evaluation and comparison of the correlation statistics using synthetic images
  • Evaluation of the correlation statistics of the real stereo PIV images