Reference : Quantifying the uncertainty in a hyperelastic soft tissue model with stochastic parameters
Scientific journals : Article
Engineering, computing & technology : Materials science & engineering
Computational Sciences
http://hdl.handle.net/10993/30946
Quantifying the uncertainty in a hyperelastic soft tissue model with stochastic parameters
English
Hauseux, Paul mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Hale, Jack mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Cotin, Stéphane [Inria Strasbourg]
Bordas, Stéphane mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
2018
Applied Mathematical Modelling
Elsevier Science
62
86-102
Yes
International
0307-904X
New York
NY
[en] We present a simple open-source semi-intrusive computational method to propagate uncertainties through hyperelastic models of soft tissues. The proposed method is up to two orders of magnitude faster than the standard Monte Carlo method. The material model of interest can be altered by adjusting few lines of (FEniCS) code. The method is able to (1) provide the user with statistical confidence intervals on quantities of practical interest, such as the displacement of a tumour or target site in an organ; (2) quantify the sensitivity of the response of the organ to the associated parameters of the material model. We exercise the approach on the determination of a confidence interval on the motion of a target in the brain. We also show that for the boundary conditions under consideration five parameters of the Ogden-Holzapfel-like model have negligible influence on the displacement of the target zone compared to the three most influential parameters. The benchmark problems and all associated data are made available as supplementary material.
FNR INTER/MOBILITY/14/8813215/CBM/Bordas
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/10993/30946
10.1016/j.apm.2018.04.021
http://doi.org/10.6084/m9.figshare.4900298
http://bitbucket.org/unilucompmech/stochastic-hyperelasticity
FP7 ; 279578 - REALTCUT - Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery
FnR ; FNR6693582 > Jack Samuel Hale > ACCeSS > Advanced Computational Methods for the Simulation of Cutting in Surgery > 01/01/2014 > 31/12/2015 > 2013

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