Particle Image Velocimetry (PIV) is currently the most widely used and well-established tool for non-invasive flow field velocity measurements, and a valuable method for validating computational fluid dynamics (CFD) models of medical devices. One of the critical steps in the CFD validation process is quantification of the experimental uncertainties. This work utilizes a new uncertainty estimation methodology developed by Charonko et al.1 for quantifying the PIV cross-correlation uncertainties. Uncertainties from experimental sources, including image magnification and acquisition timing, were propagated using Taylor series expansion for PIV data within the FDA benchmark Nozzle model2.
- Bioengineering Division
Uncertainty Estimations for Particle Image Velocimetry in a Medical Device Analog (Nozzle) Model
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Raben, JS, Hariharan, P, Robinson, R, Malinauskas, R, & Vlachos, PP. "Uncertainty Estimations for Particle Image Velocimetry in a Medical Device Analog (Nozzle) Model." Proceedings of the ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. Washington, DC, USA. September 11–13, 2013. V001T01A003. ASME. https://doi.org/10.1115/FMD2013-16164
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