Reference : SOniCS: Develop intuition on biomechanical systems through interactive error controll...
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Engineering, computing & technology : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/52913
SOniCS: Develop intuition on biomechanical systems through interactive error controlled simulations
English
Mazier, Arnaud mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
El Hadramy, Sidaty []
Brunet, Jean-Nicolas []
Hale, Jack mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Cotin, Stephane []
Bordas, Stéphane mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
2022
Submitted preprint
No
[en] This new approach allows the user to experiment with model choices
easily and quickly without requiring in-depth expertise, as constitutive models can be modified by one line of code only. This ease in building new models makes SOniCS ideal to develop surrogate, reduced order mod- els and to train machine learning algorithms for uncertainty quantification or to enable patient-specific simulations. SOniCS is thus not only a tool that facilitates the development of surgical training simulations but also, and perhaps more importantly, paves the way to increase the intuition of users or otherwise non-intuitive behaviors of (bio)mechanical systems. The plugin uses new developments of the FEniCSx project enabling au- tomatic generation with FFCx of finite element tensors such as the local residual vector and Jacobian matrix. We validate our approach with nu- merical simulations such as manufactured solutions, cantilever beams, and benchmarks provided by FEBio. We reach machine precision accuracy and demonstrate the use of the plugin for a real-time haptic simulation involv- ing a surgical tool controlled by the user in contact with a hyperelastic liver. We include complete examples showing the use of our plugin for sim- ulations involving Saint Venant-Kirchhoff, Neo-Hookean, Mooney-Rivlin, and Holzapfel Ogden anisotropic models as supplementary material.
EU H2020 DRIVEN 811099
http://hdl.handle.net/10993/52913
https://arxiv.org/abs/2208.11676
H2020 ; 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design
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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