Titlebook: Uncertainty Management for Robust Industrial Design in Aeronautics; Findings and Best Pr Charles Hirsch,Dirk Wunsch,Jordi Pons-Prats Book 2

Pelvic-Floor

General Introduction to Polynomial Chaos and Collocation Methodshe collocation method. UQ deals with the propagation of uncertainties through complex numerical models, and in the present context of the UMRIDA project, mostly computational fluid dynamics (CFD) codes. The focus is on non-intrusive methods implying that the model does not require any changes and ca

UNT

Generalized Polynomial Chaos for Non-intrusive Uncertainty Quantification in Computational Fluid Dynpose of propagating uncertainties pertaining to geometrical and/or operational parameters. Generalized homogeneous chaos expansions are considered and different techniques for the non-intrusive reconstruction of the polynomial expansion coefficients are outlined. A sparsity-based reconstruction appr

Tremor

Non-intrusive Probabilistic Collocation Method for Operational, Geometrical, and Manufacturing Uncerinties and uncertainties resulting from manufacturing variability, which are characterized by correlations of the measured coordinates. The non-intrusive probabilistic collocation method is combined with a sparse grid approach to drastically reduce the computational cost. This is one of the key feat

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Non-intrusive Uncertainty Quantification by Combination of Reduced Basis Method and Regression-based the regression-based non-intrusive polynomial chaos approach. The key idea is to retrieve the optimal orthogonal basis via inexpensive calculations on a coarse mesh and then use them for the fine-scale analysis. The reduced basis approach was applied to a highly nonlinear analytical test function,

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Screening Analysis and Adaptive Sparse Collocation Methodl techniques for screening analysis (SS-ANOVA, PCA, and Morris) that can be used in order to reduce the number of uncertain parameters to the most significant ones in the problem, and an adaptive version of the Polynomial Chaos Expansion (PCE) that can be used to reduce significantly the number of s

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Comparing Surrogates for Estimating Aerodynamic Uncertainties of Airfoilso geometric input uncertainties. A comparison with direct integration and polynomial chaos methods is also performed. The aerodynamic coefficients and their partial gradients with respect to the uncertain input parameters are computed with a CFD solver and its adjoint counterpart. Reference statisti

ESO

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