  This work aims at identifying and quantifying uncertainties related to
elastic and viscoelastic parameters, which characterize the arterial wall
behavior, in one-dimensional modeling of the human arterial hemodynamics. The
chosen uncertain parameters are modeled as random Gaussian-distributed
variables, making stochastic the system of governing equations. The proposed
methodology is initially validated on a model equation, presenting a thorough
convergence study which confirms the spectral accuracy of the stochastic
collocation method and the second-order accuracy of the IMEX finite volume
scheme chosen to solve the mathematical model. Then, univariate and
multivariate uncertain quantification analyses are applied to the a-FSI blood
flow model, concerning baseline and patient-specific single-artery test cases.
A different sensitivity is depicted when comparing the variability of flow rate
and velocity waveforms to the variability of pressure and area, the latter ones
resulting much more sensitive to the parametric uncertainties underlying the
mechanical characterization of vessel walls. Simulations performed considering
both the simple elastic and the more realistic viscoelastic constitutive law
show that the great uncertainty of the viscosity parameter plays a major role
in the prediction of pressure waveforms, enlarging the confidence interval of
this variable. In-vivo recorded patient-specific pressure data falls within the
confidence interval of the output obtained with the proposed methodology and
expectations of the computed pressures are comparable to the recorded
waveforms.
