Analysis of uncertainty and variability in finite element computational models for biomedical engineering: characterization and propagation

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis an...

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Detalles Bibliográficos
Autores: Mangado López, Nerea, Piella Fenoy, Gemma, Noailly, Jérôme, Pons-Prats, Jordi, González Ballester, Miguel Ángel, 1973-
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/33931
Acceso en línea:http://hdl.handle.net/10230/33931
http://dx.doi.org/10.3389/fbioe.2016.00085
Access Level:acceso abierto
Palabra clave:Uncertainty quantification
Finite element models
Random variables
Intrusive and non-intrusive methods
Sampling techniques
Computational modeling
Descripción
Sumario:Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.