Flowfield vorticity calculation using PIV data

The simultaneous velocity measurement at different flowfield locations is one of the key advantages of a PIV system. This allows a straightforward calculation of derived flow magnitudes including spatial correlations. Thus, postprocessing techniques need further attention in order to assure maximum feature extraction with minimum error, among other issues. This paper is devoted to expand the capability of calculating vorticity in a PIV sampled flow field. The methodology proposed is based on linear algorithms (FIR filters) able to obtain the first spatial derivative of a grid sampled magnitude containing random noise. Generalization to other flow magnitudes based on spatial derivatives is immediate. Been this a widely used method, the main objective of the study is to develop new filters from families already documented. The relevant performance parameters of these filters are evaluated and commented. Synthetic data fields are used to test the basic metrological attributes in a controlled way. As a result of the study, algorithms with better performances than the usual ones are proposed and strong points are highlighted. Finally, results of the application to real PIV data are exhibited and commented.