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CEMRACS 2004 - Centre d'été de Mathématiques et Recherche Avancées en Calcul scientifique : Mathematics and applications to biology and medicine, Marseille : France (2004)
Parameter identification for a one-dimensional blood flow model
Jean-Frédéric Gerbeau 1, Vincent Martin 1, 2, Astrid Decoene 3, Clément François 4
(2005)

The purpose of this work is to use a variational method to identify some of the parameters of one-dimensional models for blood flow in arteries. These parameters can be fit to approach as much as possible some data coming from experimental measurements or from numerical simulations performed using more complex models. A nonlinear least squares approach to parameter estimation was taken, based on the optimization of a cost function. The resolution of such an optimization problem generally requires the efficient and accurate computation of the gradient of the cost function with respect to the parameters. This gradient is computed analytically when the one-dimensional hyperbolic model is discretized with a second order Taylor-Galerkin scheme. An adjoint approach was used. Some preliminary numerical tests are shown. In these simulations, we mainly focused on determining a parameter that is linked to the mechanical properties of the arterial walls, the compliance. The synthetic data we used to estimate the parameter were obtained from a numerical computation performed with a more accurate model: a three-dimensional fluid-structure interaction model. The first results seem to be promising. In particular, it is worth noticing that the estimated compliance which gives the best fit is quite different from the values that are commonly used in practice.
1:  REO (INRIA Paris-Rocquencourt)
INRIA – Laboratoire Jacques-Louis Lions
2:  Laboratoire de Mathématiques Appliquées de Compiègne - EA2222 (LMAC)
Université de Technologie de Compiègne
3:  Laboratorio di Modellistica e Calcolo Scientifico MOX (Dipartimento di Matematica "Francesco Brioschi")
Politecnico di Milano
4:  ESTIME (INRIA Paris-Rocquencourt)
INRIA
Mathematics/Numerical Analysis