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Boundary control in computational haemodynamics

Published online by Cambridge University Press:  21 May 2018

Taha S. Koltukluoğlu Open the ORCID record for Taha S. Koltukluoğlu [Opens in a new window]  and
Pablo J. Blanco
Taha S. Koltukluoğlu*
Affiliation:
Seminar for Applied Mathematics, Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland
Pablo J. Blanco
Affiliation:
National Laboratory for Scientific Computing, (LNCC/MCTIC), 25651-075 Petrópolis, Brazil
*
†Email addresses for correspondence: [email protected], [email protected]
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Abstract

In this work, a data assimilation method is proposed following an optimise-then-discretise approach, and is applied in the context of computational haemodynamics. The methodology aims to make use of phase-contrast magnetic resonance imaging to perform optimal flow control in computational fluid dynamic simulations. Flow matching between observations and model predictions is performed in luminal regions, excluding near-wall areas, improving the near-wall flow reconstruction to enhance the estimation of related quantities such as wall shear stresses. The proposed approach remarkably improves the flow field at the aortic root and reveals a great potential for predicting clinically relevant haemodynamic phenomenology. This work presents model validation against an analytical solution using the standard 3-D Hagen–Poiseuille flow, and validation with real data involving the flow control problem in a glass replica of a human aorta imaged with a 3T magnetic resonance scanner. In vitro experiments consist of both a numerically generated reference flow solution, which is considered as the ground truth, as well as real flow MRI data obtained from phase-contrast flow acquisitions. The validation against the in vitro flow MRI experiments is performed for different flow regimes and model parameters including different mesh refinements.

JFM classification

Biological Fluid Dynamics: Blood flow Flow Control: Control theory Mathematical Foundations: Variational methods
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 847 , 25 July 2018 , pp. 329 - 364
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Copyright
© 2018 Cambridge University Press 

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