z-logo
open-access-imgOpen Access
The influence of flow model selection on finite element model parameter estimation using Bayesian inference
Author(s) -
Paul J. Hadwin,
Byron D. Erath,
Sean D. Peterson
Publication year - 2021
Publication title -
jasa express letters
Language(s) - English
Resource type - Journals
ISSN - 2691-1191
DOI - 10.1121/10.0004260
Subject(s) - bernoulli's principle , bayesian inference , finite element method , estimation theory , model selection , sensitivity (control systems) , kinematics , flow (mathematics) , fluid dynamics , computer science , bayes estimator , bayesian probability , mathematics , mechanics , algorithm , artificial intelligence , engineering , physics , structural engineering , geometry , classical mechanics , electronic engineering , aerospace engineering
Recently, Bayesian estimation coupled with finite element modeling has been demonstrated as a viable tool for estimating vocal fold material properties from kinematic information obtained via high-speed video recordings. In this article, the sensitivity of the parameter estimations to the employed fluid model is explored by considering Bernoulli and one-dimensional viscous fluid flow models. Simulation results indicate that prescribing an ad hoc separation location for the Bernoulli flow model can lead to large estimate biases, whereas including the separation location as an estimated parameter leads to results comparable to that of the viscous fluid flow model.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom