  The choice of appropriate boundary conditions is a fundamental step in
computational fluid dynamics (CFD) simulations of the cardiovascular system.
Boundary conditions, in fact, highly affect the computed pressure and flow
rates, and consequently haemodynamic indicators such as wall shear stress,
which are of clinical interest. Devising automated procedures for the selection
of boundary conditions is vital to achieve repeatable simulations. However, the
most common techniques do not automatically assimilate patient-specific data,
relying instead on expensive and time-consuming manual tuning procedures. In
this work, we propose a technique for the automated estimation of outlet
boundary conditions based on optimal control. The values of resistive boundary
conditions are set as control variables and optimized to match available
patient-specific data. Experimental results on four aortic arches demonstrate
that the proposed framework can assimilate 4D-Flow MRI data more accurately
than two other common techniques based on Murray's law and Ohm's law.
