title: Simulation-based uncertainty quantification of human arterial network hemodynamics.
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.
authors: Modelling 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
authors: Peng
authors: P
authors: Chen
authors: Alfio
authors: A
authors: Quarteroni
authors: Gianluigi
authors: G
authors: Rozza
mesh_terms: D001158:Arteries / Q000033:anatomy & histology / Q000502:physiology*; D001696:Biomechanical Phenomena; D003198:Computer Simulation; D006439:Hemodynamics / Q000502:physiology*; D006801:Humans; D008955:Models, Cardiovascular; D013269:Stochastic Processes