TY - JOUR
T1 - Determining velocity from tagging velocimetry images using optical flow
AU - Gevelber, T. S.
AU - Schmidt, B. E.
AU - Mustafa, M. A.
AU - Shekhtman, D.
AU - Parziale, N. J.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/6
Y1 - 2022/6
N2 - In this work, we present the application of wavelet-based optical flow velocimetry (wOFV) to tagging velocimetry image data. wOFV is demonstrated to compare favorably to cross-correlation on experimental two-dimensional Krypton tagging velocimetry (KTV-2D) images from a Mach 2.75 turbulent shock wave-boundary layer interaction. Results from both methods show good agreement for the mean velocity field, while wOFV has several advantages compared to cross-correlation including increased spatial resolution as well as robustness and simplicity of implementation. The performance of wOFV on tagging velocimetry images is evaluated quantitatively using a set of simulated data from a turbulent boundary layer including images and specified velocity fields. wOFV is found to produce accurate results for turbulence statistics using write images with parallel 1D lines and is relatively insensitive to moderate amounts of noise. Additionally, it can accurately calculate two-dimensional velocity fields over the entire image domain for images containing sets of intersecting write lines, as well as derivative quantities such as vorticity, as long as the line spacing is sufficiently small. Graphical abstract: [Figure not available: see fulltext.]
AB - In this work, we present the application of wavelet-based optical flow velocimetry (wOFV) to tagging velocimetry image data. wOFV is demonstrated to compare favorably to cross-correlation on experimental two-dimensional Krypton tagging velocimetry (KTV-2D) images from a Mach 2.75 turbulent shock wave-boundary layer interaction. Results from both methods show good agreement for the mean velocity field, while wOFV has several advantages compared to cross-correlation including increased spatial resolution as well as robustness and simplicity of implementation. The performance of wOFV on tagging velocimetry images is evaluated quantitatively using a set of simulated data from a turbulent boundary layer including images and specified velocity fields. wOFV is found to produce accurate results for turbulence statistics using write images with parallel 1D lines and is relatively insensitive to moderate amounts of noise. Additionally, it can accurately calculate two-dimensional velocity fields over the entire image domain for images containing sets of intersecting write lines, as well as derivative quantities such as vorticity, as long as the line spacing is sufficiently small. Graphical abstract: [Figure not available: see fulltext.]
UR - http://www.scopus.com/inward/record.url?scp=85131226601&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85131226601&partnerID=8YFLogxK
U2 - 10.1007/s00348-022-03448-z
DO - 10.1007/s00348-022-03448-z
M3 - Article
AN - SCOPUS:85131226601
SN - 0723-4864
VL - 63
JO - Experiments in Fluids
JF - Experiments in Fluids
IS - 6
M1 - 104
ER -