Determining velocity from tagging velocimetry images using optical flow

T. S. Gevelber, B. E. Schmidt, M. A. Mustafa, D. Shekhtman, N. J. Parziale

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.]

Original languageEnglish
Article number104
JournalExperiments in Fluids
Volume63
Issue number6
DOIs
StatePublished - Jun 2022

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