A velocity tracking approach for the data assimilation problem in blood flow simulations. (14th February 2017)

• Record Type: Journal Article
• Authors: Tiago, J.; Guerra, T.; Sequeira, A.
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 33:Number 10(2017:Oct.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-02-14
• Subjects: blood flow -- boundary control -- data assimilation -- sequential quadratic programming; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.2856
• Languages: English
• ISSNs: 2040-7939

Abstract

Abstract: Several advances have been made in data assimilation techniques applied to blood flow modeling. Typically, idealized boundary conditions, only verified in straight parts of the vessel, are assumed. We present a general approach, on the basis of a Dirichlet boundary control problem, that may potentially be used in different parts of the arterial system. The relevance of this method appears when computational reconstructions of the 3D domains, prone to be considered sufficiently extended, are either not possible, or desirable, because of computational costs. On the basis of taking a fully unknown velocity profile as the control, the approach uses a discretize then optimize methodology to solve the control problem numerically. The methodology is applied to a realistic 3D geometry representing a brain aneurysm. The results show that this data assimilation approach may be preferable to a pressure control strategy and that it can significantly improve the accuracy associated to typical solutions obtained using idealized velocity profiles. Abstract : We present a general data assimilation approach, on the basis of a Dirichlet boundary control problem, that may potentially be used in different parts of the arterial system. The relevance of this method appears when computational reconstructions of the 3D domains, prone to be considered sufficiently extended to obtain reliable solutions, are not possible. The methodology is applied to a realistic 3D geometry representing a brain aneurysm.