A versatile incompressible Navier-Stokes solver for blood flow application

We present in this paper an integrated approach to compute quickly an incompressible Navier-Stokes (NS) flow in a section of a large blood vessel using medical imaging data. The goal is essentially to provide a first-order approximation of some main quantities of interest in cardiovascular disease: the shear stress and the pressure on the wall. The NS solver relies on the L₂ penalty approach pioneered by Caltagirone and co-workers and combines nicely with a level set method based on the Mumford-Shah energy model. Simulations on stenosis cases based on angiogram are run in parallel with MatlabMPI on a shared-memory machine. While MatlabMPI communications are based on the load and save functions of Matlab and have high latency indeed, we show that our Aitken-Schwarz domain decomposition algorithm provides a good parallel efficiency and scalability of the NS code.