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Updated: May 11, 2026

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom
Published on: February 25, 2022
Simulation-based uncertainty quantification of human arterial network hemodynamics
Peng Chen1, Alfio Quarteroni, Gianluigi Rozza
1Modelling and Scientific Computing, Mathematics Institute of Computational Science and Engineering-MATHICSE, Ecole Polytechnique Fédérale de Lausanne-EPFL, Station 8, CH-1015 Lausanne, Switzerland. peng.chen@epfl.ch
Abstract:
This work aims at identifying and quantifying uncertainties from various sources in human cardiovascular system based on stochastic simulation of 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 systemically the statistics and sensitivity of the solution with respect to many different uncertainties in a relatively complete arterial network with potential physiological and pathological implications for the first time.
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