background-oriented schlieren (BOS)
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We propose an improved density integration methodology for Background Oriented Schlieren (BOS) measurements that overcomes the noise sensitivity of the commonly used Poisson solver. The method employs a weighted least-squares (WLS) optimization of the 2D integration of the density gradient field by solving an over-determined...

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 of view. Displacement uncertainty quantification algorithms from cross-correlation-based particle image velocimetry are used to...

We present a ray tracing image generation methodology for rendering realistic images of particle image velocimetry (PIV) and background oriented schlieren (BOS) experiments in the presence of density/refractive index gradients. This methodology enables the simulation of experiments for experimental design, error, and uncertainty analysis. Images...

Background-Oriented Schlieren (BOS) is used to measure fluid density from the apparent distortion of a target dot pattern. Here, we propose a new displacement estimation methodology based on tracking individual dots on the pattern as opposed to conventional cross-correlation algorithms. As dot patterns used in...

Background-Oriented Schlieren (BOS) is a technique used to measure fluid density from the apparent distortion of a target dot pattern. Here, we model how non-linearities in the density gradient fields can blur the dot pattern image and increase the position uncertainty. To develop this model,...