Uncertainty quantification of the human arterial network
Friday 14th December 2012
Peng Chen, Alfio Quarteroni, Gianluigi Rozza
This work aims at identifying and quantifying uncertainties from various sources in human cardiovascular system based on a one dimensional arterial network. A general analysis of different uncertainties and probability characterization with log-normal distribution of these uncertainties is introduced. Deriving from a deterministic one dimensional fluid structure interaction model, we establish the stochastic model as a coupled hyperbolic system incorporated with parametric uncertainties to describe the blood flow and pressure wave propagation in the arterial network. By applying a stochastic collocation method with sparse grid technique, we study systematically the statistics and sensitivity of the solution with respect to many different uncertainties in a relatively complete arterial network validated against clinical measurements for the first time.