Wavelet-based optical flow velocimetry (Wofv) applied to tagging velocimetry data

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents 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 synthetic data including images and specified velocity fields. wOFV is highly accurate in regions of the images near the intersection of write lines, with median error vector magnitudes below 5%. Errors in the instantaneous measurements of the velocity fluctuations and vorticity are higher, with median values between 20 and 50%.

Original languageEnglish
Title of host publicationAIAA Scitech 2021 Forum
Pages1-13
Number of pages13
StatePublished - 2021
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 - Virtual, Online
Duration: 11 Jan 202115 Jan 2021

Publication series

NameAIAA Scitech 2021 Forum

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021
CityVirtual, Online
Period11/01/2115/01/21

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