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 L 2 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. Copyright © 2006 John Wiley & Sons, Ltd.