Inverse problems in fluid dynamics for enhanced velocimetry

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• Alexandros Kontogiannis (University of Cambridge)
• Thursday 16 February 2023, 11:30-12:30
• Open Plan Area, Institute for Energy and Environmental Flows, Madingley Rise CB3 0EZ.

If you have a question about this talk, please contact Catherine Pearson.

We formulate a digital twin approach to the reconstruction of noisy and sparse velocity images. The method learns the most probable fluid dynamics model that fits the data by solving a Bayesian inverse Navier–Stokes boundary value problem. This jointly reconstructs and segments the velocity field, and at the same time infers hidden quantities such as the hydrodynamic pressure and the wall shear stress. Using a Bayesian framework, we regularize the problem by introducing a priori information about the unknown parameters in the form of Gaussian random fields. This further allows us to estimate the uncertainties of the unknowns by approximating their posterior covariance with a quasi-Newton method. Although this method has been developed for magnetic resonance velocimetry (flow-MRI), it extends to other velocimetry methods such as ultrasound Doppler velocimetry, particle image velocimetry (PIV) and scalar image velocimetry (SIV).

This talk is part of the Institute for Energy and Environmental Flows (IEEF) series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Energy Seminars
• Department of Earth Sciences seminars
• Institute for Energy and Environmental Flows (IEEF)
• NanoDTC Energy Materials Talks
• Open Plan Area, Institute for Energy and Environmental Flows, Madingley Rise CB3 0EZ
• history
• ps635

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