Bayesian sensitivity analysis of a nonlinear finite element model

Becker, W.; Oakley, Jeremy E.; Surace, Cecilia; Gili, Piero; Rowson, Jennifer; Worden, Keith

doi:10.1016/j.ymssp.2012.03.009

Cited by 41 publications

(22 citation statements)

References 20 publications

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“…Despite these uncertainties, MV models can provide insights unattainable from experiments alone, as George Box once said, “All models are wrong, but some are useful.” To make the models meaningful, we need to address the model uncertainty in a rational way. Recently, statistics inference, such as Monte Carlo methods and the Gaussian process emulator, has been actively applied in many areas to quantify model uncertainty. Such an approach can provide confidence intervals of predictions with probability distributions of model inputs inferred from limited data sets .…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Modelling mitral valvular dynamics–current trend and future directions

Gao

Feng

et al. 2017

Numer Methods Biomed Eng

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Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state‐of‐the‐art modelling of the mitral valve, including static and dynamics models, models with fluid‐structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Modelling mitral valvular dynamics–current trend and future directions

Gao

Feng

et al. 2017

Numer Methods Biomed Eng

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show abstract

“…These parameters were selected because they are sources of significant uncertainty and interest, data is readily available concerning their upper and lower limits, and they can be easily varied within the LS-Dyna input file. Some other parameters such as leaflet thickness were discounted due to results from a previous study (Becker et al, 2008), and the lack of available data. Thubrikar quotes the ranges of l* and C5L, which are known to vary from person to person (Thubrikar, 1990).…”

Section: Uncertainty Analysismentioning

confidence: 99%

Bayesian sensitivity analysis of a model of the aortic valve

Becker¹,

Rowson²,

Oakley³

et al. 2011

Journal of Biomechanics

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“…A completely general framework for Bayesian sensitivity analysis can be found in [110]. Recent applications can be found in [111,112]; the first looks at a nonlinear FE model of a heart valve; the second looks at the design of a system for detecting hard landings for aircraft landing gear.…”

Section: Sensitivity-based Methodsmentioning

confidence: 99%