Premium
Simulation‐based uncertainty quantification of human arterial network hemodynamics
Author(s) -
Chen Peng,
Quarteroni Alfio,
Rozza Gianluigi
Publication year - 2013
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.2554
Subject(s) - sparse grid , uncertainty quantification , parametric statistics , collocation (remote sensing) , sensitivity (control systems) , computer science , mathematical optimization , probability distribution , mathematics , engineering , statistics , machine learning , electronic engineering
SUMMARY 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. Copyright © 2013 John Wiley & Sons, Ltd.