subject: background oriented schlieren type: dataset
10.4231/D2FC-N191
Jiacheng Zhang , Lalit Rajendran , Pavlos Vlachos , Sally P M Bane , Sayantan Bhattacharya
05/18/2021
We present an uncertainty quantification methodology for density estimation from background-oriented Schlieren (BOS) measurements, in order to provide local, instantaneous, a posteriori uncertainty bounds on each density measurement in the field...
Aeronautics and Astronautics Engineering background oriented schlieren Numerical Analysis Python uncertainty quantification
10.4231/DV5G-5186
06/26/2020
Propose a model to describe the effect of density/refractive index gradients on reducing the measurement precision of background-oriented schlieren (BOS) experiments by deriving the Cramer–Rao lower bound (CRLB) for the 2D centroid estimation...
background oriented schlieren cramer-rao lower bound uncertainty quantification
10.4231/P45Z-8361
08/26/2020
Ray tracin based image generation methodology to render realistic images of particle image velocimetry (PIV) and background oriented schlieren (BOS) experiments in the presence of density/refractive index gradients.
Aeronautics and Astronautics Engineering background oriented schlieren cuda particle image velocimetry Python ray tracing
10.4231/X101-WK63
Lalit Rajendran , Pavlos Vlachos , Sally P M Bane
05/18/2021
A dot tracking method to process BOS images that improves the accuracy, precision, and spatial resolution of the measurements
Aeronautics and Astronautics Engineering background oriented schlieren image processing Matlab particle tracking velocimetry
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