measurement science
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The uncertainty in a planar PIV measurement has been a topic of great interest in the last decade. Here, we present a new direct uncertainty estimation method for Particle Image Velocimetry (PIV), that uses the correlation plane as a model for the probability density function...

Volumetric Particle Tracking Velocimetry (PTV) non-invasively measures the 3D velocity field by recording successive snapshots of the tracer particle motion using a multi-camera set-up. A key step in the measurement chain is reconstructing the 3D particle location using the multi-camera projected particle images. However, the...

PIV uncertainty quantification is important for comparison with CFD simulations and engineering design, but is challenging due to the complex non-linear measurement chain which involves a large number of parameters. Multiple assessments show that none of the current methods can reliably predict the actual uncertainty...

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,...