@article {25229,
	title = {Variational data assimilation for transient blood flow simulations},
	journal = { International Journal for Numerical Methods in Biomedical Engineering},
	volume = {35},
	year = {2018},
	month = {10/2018},
	pages = {e3152},
	publisher = {John Wiley \& Sons},
	abstract = {Several cardiovascular diseases are caused from localised abnormal blood flow\&nbsp;such as in the case of stenosis or aneurysms. Prevailing theories propose that the development is caused by abnormal wall-shear stress in focused\&nbsp;areas. \&nbsp;Computational fluid mechanics have arisen as a promising tool for\&nbsp;a more precise and quantitative analysis, in particular because the\&nbsp;anatomy is often readily available even by standard imaging techniques such as magnetic resolution and computed tomography angiography. \&nbsp;However,\&nbsp;computational fluid mechanics rely on accurate initial and boundary conditions which\&nbsp;is difficult to obtain. \&nbsp;In this paper we address the problem of recovering high resolution information from noisy, low-resolution\&nbsp;measurements of blood flow using variational data assimilation based on a transient Navier-Stokes model.\&nbsp;Numerical experiments are performed in both 2D and 3D and with pulsatile flow relevant for physiological flow in cerebral aneurysms.\&nbsp;The results demonstrate that, with suitable regularisation, the model accurately reconstructs flow, even in the presence of significant noise.\&nbsp;},
	keywords = {adjoint equations, blood flow, Finite element method, Navier-Stokes, optimal control, variational data assimilation},
	author = {Simon W {Funke} and Nordaas, Magne and Evju, {\O}yvind and Martin Sandve {Aln{\ae}s} and Mardal, Kent-Andre}
}
