Some advances on anchored ANOVA expansion for high order moments computation
TANG, Kunkun
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
CONGEDO, Pietro Marco
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
ABGRALL, Rémi
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
TANG, Kunkun
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
CONGEDO, Pietro Marco
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
ABGRALL, Rémi
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
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Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Langue
en
Communication dans un congrès
Ce document a été publié dans
6th European Conference on Computational Fluid Dynamics (ECCOMAS CFD 2014), 2014-07-20, Barcelona. 2014-07-20
Résumé en anglais
Covariance decomposition of output variance is used in this paper to take account of interactions between non-orthogonal components in anchored ANOVA method. Results show this approach is less sensitive to the anchor ...Lire la suite >
Covariance decomposition of output variance is used in this paper to take account of interactions between non-orthogonal components in anchored ANOVA method. Results show this approach is less sensitive to the anchor reference point than existing method. Covariance-based sensitivity indices (SI) are also used, compared to variance-based SI. Furthermore, we emphasize covariance decomposition can be generalized in a straightforward way to decompose high order moments.< Réduire
Mots clés en anglais
stochastic problems
uncertainty quantification
(anchored) ANOVA
global sensitivity analysis
variance/covariance decomposition
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