Comparative assessment of PIV-based pressure evaluation techniques applied to a transonic base flow
P Blinde
D Michaelis (LaVision)
Bas van Oudheusden (TU Delft - Aerospace Engineering)
P.E. Weiss (Office National d'Etudes et de Recherches Aerospatiales)
Roeland de Kat (University of Southhampton)
A. Laskari (University of Southhampton)
Y.J. Jeon (Université de Poitiers)
L David (Université de Poitiers)
D Schanz (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
F. Huhn (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
S Gesemann (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Matteo Novara (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
C. McPhaden (Queen’s University)
N. Neeteson (Queen’s University)
D. Rival (Queen’s University)
Jan Schneiders (TU Delft - Aerospace Engineering)
Ferdinand Schrijer (TU Delft - Aerospace Engineering)
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Abstract
A test case for PIV-based pressure evaluation techniques has been developed by constructing a simulated experiment from a ZDES simulation for an axisymmetric base flow at Mach 0.7. The test case comprises sequences of four subsequent particle images (representing multi-pulse data) as well as continuous time-resolved data. Particle images were processed using tomographic PIV processing as well as the PTV algorithm ‘Shake-The-Box’. Multiple pressure reconstruction techniques have subsequently been applied to the PIV results (Eulerian approach, iterative least-square pseudo-tracking, Taylor’s hypothesis approach, instantaneous Vortex-in-Cell) and PTV results (FlowFit, Vortex-in-Cell-plus, Voronoi-based pressure evaluation and iterative least-square pseudo-tracking). All methods were able to reconstruct the main features of the instantaneous pressure fields, including methods that reconstruct pressure from a single PIV velocity snapshot. Highly accurate pressure field reconstructions could be obtained by using PTV approaches in combination with more advanced techniques. In general, the use of longer series of time-resolved input data, when available, allows more accurate pressure field reconstruction. Noise in the input data typically reduces the accuracy of the reconstructed pressure fields, but none of the techniques was found to be critically sensitive to the amount of noise added in the present test case