Benchmarking Uncertainty Quantification Methods Using the NACA 2412 Airfoil with Geometrical and Operational Uncertainties
| Autor: | Matteo Diez, Charles Hirsch, Michele Pisaroni, Kyung K. Choi, Frederick Stern, Nicholas J. Gaul, Umberto Iemma, Andrea Serani, Luca Montagliani, Pénélope Leyland, Dirk Wunsch, Domenico Quagliarella, Jaekwan Shin |
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| Přispěvatelé: | AIAA AVIATION Forum, Quagliarella, Domenico, Serani, Andrea, Diez, Matteo, Pisaroni, Michele, Leyland, Penelope, Montagliani, Luca, Iemma, Umberto, Gaul, Nicholas J., Shin, Jaekwan, Wunsch, Dirk, Hirsch, Charle, Choi, Kk, Stern, Frederick |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | 20th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Dallas, USA, 17-21/06/2019 info:cnr-pdr/source/autori:Domenico Quagliarella (1); Andrea Serani (2); Matteo Diez (2); Michele Pisaroni (3); Pénélope Leyland (3); Luca Montagliani (4); Umberto Iemma (4); Nicholas J. Gaul (5); Jaekwan Shin (5); Dirk Wunsch (6); Charles Hirsch (6); KK Choi (7); Frederick Stern (7)/congresso_nome:20th AIAA%2FISSMO Multidisciplinary Analysis and Optimization Conference/congresso_luogo:Dallas, USA/congresso_data:17-21%2F06%2F2019/anno:2019/pagina_da:/pagina_a:/intervallo_pagine |
| Popis: | This paper presents uncertainty quantification (UQ) benchmarking activities within the NATO AVT-252 Task Group on "Stochastic Design Optimization for Naval and Aero Military Vehicles." UQ methods are assessed and compared as an essential part of stochastic optimization procedures. Several metamodel (dynamic radial basis functions, dynamic Kriging, Gaussian process), Monte Carlo (multi-level Monte Carlo) and collocation (non-intrusive stochastic collocation) methods are applied to 2D and 15D UQ problems (that is with 2 or 15 uncertainties) of a NACA 2412 airfoil subject to operational (Mach number) and geometrical (design variables) uncertainties, both in the subsonic and transonic regimes. The flow is solved by MSES, XFoil, and the FINE TM /Open suite. A pure Monte Carlo simulation based on more than 300,000 samples is used as a benchmark to assess the accuracy and efficiency of UQ methods. These can provide satisfactory results with errors for the expected value and standard deviation of C D smaller than 0.5 and 5% respectively. |
| Databáze: | OpenAIRE |
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