Fluid Dynamics
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Silicone Sylgard 184 (PDMS) is commonly used when manufacturing geometries for bioflow studies due to its optical transparency and compliant nature. However, for use with particle image velocimetry (PIV), a suitable blood analog working fluid is needed which both matches the physical properties of blood...

4D flow magnetic resonance imaging (MRI) allows for in vivo acquisition of time-resolved three-dimensional (3D) blood flow, thus enabling quantitative analysis of volumetric, time-varying hemodynamic quantities such as flow rates, wall shear stress (WSS), pressure difference, etc. 4D flow MRI is based on the phase...

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...

Pressure measured from the cardiovascular system is widely used to diagnose disease. Pressure reconstruction methods are increasingly of interest with the development of 4D flow magnetic resonance imaging (MRI) which noninvasively measures time-resolved velocity fields in-vivo. However, several error sources and limitations inherent to in...

This article presents a method for three-dimensional confocal microscopy to study the kinematics of nanometer-sized molecules and particles that are of great interest to a wide range of biological systems and cellular mechanics but have heretofore been obscured by limitations in measurement technology. The correlation-based...

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...