  We present validation of benchmark experimental data for computational fluid
dynamics (CFD) analyses of medical devices using advanced Particle Image
Velocimetry (PIV) processing and post-processing techniques. This work is an
extension of a previous FDA-sponsored multi-laboratory study, which used a
medical device mimicking geometry referred to as the FDA benchmark nozzle
model. Time-resolved PIV analysis was performed in five overlapping regions of
the model for Reynolds numbers in the nozzle throat of 500, 2,000, 5,000, and
8,000. Images included a two-fold increase in spatial resolution in comparison
to the previous study. Data was processed using ensemble correlation, dynamic
range enhancement, and phase correlations to increase signal-to-noise ratios
and measurement accuracy, and to resolve flow regions with large velocity
ranges and gradients, which is typical of many blood-contacting medical
devices. Parameters relevant to device safety, including shear stress at the
wall and in bulk flow, were computed using radial basis functions (RBF) to
improve accuracy. In-field spatially resolved pressure distributions, Reynolds
stresses and energy dissipation rates were computed from PIV measurements.
Velocity measurement uncertainty was estimated directly from the PIV
correlation plane, and uncertainty analysis for wall shear stress at each
measurement location was performed using a Monte Carlo model. (truncated
abstract)
