Accuracy and speed assessment of 3D cross-correlation algorithms for two-frame and multi-frame PIV
Résumé
The need to extract higher order volumetric experimental data from PIV such as acceleration and pressure fields benefits from fast and accurate cross-correlation methods. This paper reexamines the application of two-dimensional (2D) cross-correlation methods to three-dimensional datasets by Bilsky et al. [3] and the binning techniques of Discetti et al. [7]. A robust version of the 2D methods, which reconstructs the three-dimensional (3D) signal from the 2D cross correlation maps is proposed. This method is then extended to the the fluid trajectory evaluation from ensemble-averaged cross-correlation (FTEE) method. Performance tests based on computational time and accuracy for both two-frame and multi-frame PIV were carried out on synthetically generated data, where the errors and correlation signal can be investigated. The cases presented herein include uniaxial uniform linear displacements and shear, and a final comparison of the FTEE method on synthetic homogeneous isotropic turbulence (HIT) data. For the cross-correlation computation, the proposed algorithm is in the order of 10 times faster than a standard 3D FFT. The FTEE method reduces the bias and random errors in the HIT data, and we find that the proposed algorithms yields almost identical results with significant speed-up.
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