Real-time simulation of biological soft tissues: a PGD approach.
Identifieur interne : 001909 ( Main/Exploration ); précédent : 001908; suivant : 001910Real-time simulation of biological soft tissues: a PGD approach.
Auteurs : S. Niroomandi [Espagne] ; D. González ; I. Alfaro ; F. Bordeu ; A. Leygue ; E. Cueto ; F. ChinestaSource :
- International journal for numerical methods in biomedical engineering [ 2040-7947 ] ; 2013.
English descriptors
- KwdEn :
- MESH :
- anatomy & histology : Liver.
- education : Surgical Procedures, Operative.
- methods : Image Processing, Computer-Assisted.
- physiology : Liver.
- Algorithms, Computer Simulation, Feedback, Finite Element Analysis, Humans, Models, Biological, Pressure, Time Factors.
Abstract
We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary for haptic rendering. This approach is based upon the use of proper generalized decomposition techniques, a generalization of PODs. Proper generalized decomposition techniques can be considered as a means of a priori model order reduction and provides a physics-based meta-model without the need for prior computer experiments. The suggested strategy is thus composed of an offline phase, in which a general meta-model is computed, and an online evaluation phase in which the results are obtained at real time. Results are provided that show the potential of the proposed technique, together with some benchmark test that shows the accuracy of the method.
Url:
DOI: 10.1002/cnm.2544
PubMed: 23495247
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary for haptic rendering. This approach is based upon the use of proper generalized decomposition techniques, a generalization of PODs. Proper generalized decomposition techniques can be considered as a means of a priori model order reduction and provides a physics-based meta-model without the need for prior computer experiments. The suggested strategy is thus composed of an offline phase, in which a general meta-model is computed, and an online evaluation phase in which the results are obtained at real time. Results are provided that show the potential of the proposed technique, together with some benchmark test that shows the accuracy of the method.</div>
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