EAGER: In-Lab X-Ray Particle Image Velocimetry

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The ability to measure fluid flow properties non-intrusively is often crucial for providing understanding of fluid dynamics, and subsequently to enable improving industrial and medical processes and equipment for the benefit of society. Particle image velocimetry uses lasers to infer fluid velocities by tracking particles in many applications involving single phase flows. However, many multiphase flows (such as bubbly flows in the wake of a ship) are important to understand, but these flows are opaque at visible wave lengths due to the refractive interfaces between the phases. Fortuitously, at X-ray wave lengths the change in refractive index between most fluids of interest is very small; therefore, X-ray based particle image (or tracking) velocimetry can measure fluid flow properties in multiphase flows. This project will develop a practical in-lab X-ray particle image velocimetry technique. The project will combine the use of numerical modelling and experiments to hopefully enable wider utilization of in-lab X-ray particle image velocimetry for multiphase fluid dynamics research.This project will use a combination of first principle-based modelling and experiments, which together will yield a deeper understanding of the physical and technical capabilities and limitations of in-lab X-ray particle image velocimetry. The numerical modeling will utilize both established Monte Carlo codes and simpler codes based on Beer-Lambert law. The experiments will utilize photon counting X-ray detectors to determine the signal to noise ratios and introduce small tracer particles to enable velocity measurements without altering the flow. The project will develop algorithms and rules for balancing source, tracer, and detector characteristics and settings. The project will validate the in-lab X-ray particle image velocimetry technique for the canonical pipe flow.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.