Titlebook: Quantification of Uncertainty: Improving Efficiency and Technology; QUIET selected contr Marta D‘Elia,Max Gunzburger,Gianluigi Rozza Book 2

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Book 2020cent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantificati

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Surrogate-Based Ensemble Grouping Strategies for Embedded Sampling-Based Uncertainty Quantificationn by the number of (preconditioned) linear solver iterations. The approach is developed within the context of locally adaptive stochastic collocation methods, where a surrogate for the number of linear solver iterations, generated from previous levels of the adaptive grid generation, is used to pred

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Conservative Model Order Reduction for Fluid Flow,system. Therefore, the loss in energy, associated with the model reduction, remains constant in time. This results in an, overall, correct evolution of the fluid that ensures robustness of the reduced system. We evaluate the performance of the proposed method through numerical simulation of various

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Piecewise Polynomial Approximation of Probability Density Functions with Application to Uncertaintyraint to enforce positivity, and is consistent. The proposed approach is validated through numerical examples in which samples are drawn from known PDFs. The approach is also used to determine approximations of (unknown) PDFs associated with outputs of interest that depend on the solution of a stoch

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Analysis of Probabilistic and Parametric Reduced Order Models,reted as expectation. The connections of factorisations of the generalised correlation to the spectral decomposition, as well as the associated Karhunen-Loève- or proper orthogonal decomposition will be sketched. The purpose of this short note is to show the common theoretical background and pull so

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Uncertainty Quantification Applied to Hemodynamic Simulations of Thoracic Aorta Aneurysms: Sensitivrm Probability Density Functions (PDFs) on a given variation range, and then we used clinical data to construct more accurate beta PDFs. In all cases, the two input parameters appeared to have a significant influence on wall shear stresses, confirming the need of using patient-specific inlet conditi

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