Benchmarking Uncertainty Quantification Methods Using the NACA 2412 Airfoil with Geometrical and Operational Uncertainties
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Domenico Quagliarella | Andrea Serani | Jaekwan Shin | Charles Hirsch | Nicholas J. Gaul | Umberto Iemma | Frederick Stern | Michele Pisaroni | Dirk Wunsch | Matteo Diez | Pénélope Leyland | K. K. Choi | Luca Montagliani
[1] Timothy W. Simpson,et al. Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come? , 2014 .
[2] Grégory Coussement,et al. Non-intrusive Probabilistic Collocation Method for Operational, Geometrical, and Manufacturing Uncertainties in Engineering Practice , 2019 .
[3] Grégory Coussement,et al. Quantification of Combined Operational and Geometrical Uncertainties in Turbo-Machinery Design , 2015 .
[4] Haitao Liu,et al. A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design , 2017, Structural and Multidisciplinary Optimization.
[5] Pénélope Leyland,et al. A Continuation Multi Level Monte Carlo (C-MLMC) method for uncertainty quantification in compressible inviscid aerodynamics , 2017 .
[6] L. Mathelin,et al. A Stochastic Collocation Algorithm for Uncertainty Analysis , 2003 .
[7] Robert Scheichl,et al. Finite Element Error Analysis of Elliptic PDEs with Random Coefficients and Its Application to Multilevel Monte Carlo Methods , 2013, SIAM J. Numer. Anal..
[8] Leo Wai-Tsun Ng,et al. Multifidelity Uncertainty Quantification Using Non-Intrusive Polynomial Chaos and Stochastic Collocation , 2012 .
[9] Michael B. Giles,et al. Multilevel Monte Carlo Path Simulation , 2008, Oper. Res..
[10] R. M. Hicks,et al. Wing Design by Numerical Optimization , 1977 .
[11] M. Drela. XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils , 1989 .
[12] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[13] Andrea Barth,et al. Multilevel Monte Carlo method for parabolic stochastic partial differential equations , 2013 .
[14] Liang Gao,et al. A hybrid variable-fidelity global approximation modelling method combining tuned radial basis function base and kriging correction , 2013 .
[15] Andrea Barth,et al. Multi-level Monte Carlo Finite Element method for elliptic PDEs with stochastic coefficients , 2011, Numerische Mathematik.
[16] A. V. D. Vaart,et al. Asymptotic Statistics: Frontmatter , 1998 .
[17] Kyung K. Choi,et al. Metamodeling Method Using Dynamic Kriging for Design Optimization , 2011 .
[18] Karl Pearson,et al. METHOD OF MOMENTS AND METHOD OF MAXIMUM LIKELIHOOD , 1936 .
[19] Dominique Pelletier,et al. APPLICATIONS OF CONTINUOUS SENSITIVITY EQUATIONS TO FLOWS WITH TEMPERATURE-DEPENDENT PROPERTIES , 2003 .
[20] Edward N. Tinoco,et al. Summary of Data from the Sixth AIAA CFD Drag Prediction Workshop: CRM Cases 2 to 5 , 2017 .
[21] Stefan Heinrich,et al. Monte Carlo Complexity of Global Solution of Integral Equations , 1998, J. Complex..
[22] Frederick Stern,et al. Multidisciplinary Design Optimization of a 3D Composite Hydrofoil via Variable Accuracy Architecture , 2018, 2018 Multidisciplinary Analysis and Optimization Conference.
[23] H. Schlichting. Zur Enstehung der Turbulenz bei der Plattenströmung , 1933 .
[24] M. Giles,et al. Viscous-inviscid analysis of transonic and low Reynolds number airfoils , 1986 .
[25] Richard P. Dwight,et al. Uncertainty quantification for a sailing yacht hull, using multi-fidelity kriging , 2015 .
[26] Stefan Heinrich,et al. Monte Carlo Complexity of Parametric Integration , 1999, J. Complex..
[27] K. K. Choi,et al. Development and validation of a dynamic metamodel based on stochastic radial basis functions and uncertainty quantification , 2014, Structural and Multidisciplinary Optimization.
[28] Gene H. Golub,et al. Calculation of Gauss quadrature rules , 1967, Milestones in Matrix Computation.
[29] Jeroen A. S. Witteveen,et al. Probabilistic Collocation: An Efficient Non-Intrusive Approach for Arbitrarily Distributed Parametric Uncertainties , 2007 .