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Alessandro Veneziani

Emory University



Some applications of Data Assimilation in Computational Hemodynamics



September 28, 2011
3:00pm    AH 106



Abstract
 

New devices for medical imaging and measurements provide a formidable data set that can be used for validating accuracy of numerical simulations of blood flow. A different approach consists of merging these data with numerical simulations. This is anticipated to improve the accuracy of computations thanks to patient-specific measures as well as the quality of (noisy) measurements thanks to the mathematical models implemented in the numerical solvers. The outcome of this Data Assimilation (DA) process is therefore a more reliable estimation of the hemodynamics of a specific patient. Reliability is becoming a fundamental concern in computational hemodynamics as soon as scientific computing is progressively accepted as a tool for supporting decision making in clinical routine.

DA is a well established approach in meteorology and geophysics, while it is still in its infancy in hemodynamics. Different methodologies can be pursued, either based on classical stochastic estimation techniques (Kalman filter) or on variational approaches. In this talk, we will present two examples of variational DA for both assimilating available blood velocity measures into an incompressible Navier-Stokes simulation and for estimating the compliance of a vascular tissue by solving an inverse fluid-structure interaction problem.

In collaboration with: M. D'Elia (Emory University), M. Perego (Florida State University), C. Vergara (University of Bergamo).








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