On the use of kriging for enhanced data reconstruction in a separated transitional flat-plate boundary layer

Abstract

Kriging method for data reconstruction and spatial enhancement of stereo-particle image velocimetry (S-PIV) data for a transitional boundary layer with a laminar separation bubble is investigated. Particularly, the effect of various variogram models and their parameters are studied in detail. In addition, we show that missing data clusters, or black zones, which often occur in PIV measurements, can be estimated using kriging provided the data are well correlated. An important issue in PIV measurements is that built-in PIV data processing software might have problems to detect or to correct spurious erroneous vectors called “outliers.” It is shown that these outliers can be eliminated or greatly alleviated using kriging. λ2 isosurface and stream traces show that noisy vortical structures are eliminated but the main coherent structures are well preserved and smoothed, thus procedures for the detection and tracking of vortex core lines can be effectively applied on kriged data. Analytical test data for a more quantitative evaluation of the performance of kriging are given in the Appendices.