A confidence-based aerospace design approach robust to structural turbulence closure uncertainty
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Publication:2084092
DOI10.1016/j.compfluid.2022.105614OpenAlexW4291109994MaRDI QIDQ2084092
Pietro Marco Congedo, G. Gori, Olivier P. Le Maître
Publication date: 17 October 2022
Published in: Computers and Fluids (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.compfluid.2022.105614
robust optimizationaerodynamic designeigenspace perturbation methodRANS model uncertaintyturbulence closure uncertainty
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Cites Work
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- Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
- Efficient global optimization of expensive black-box functions
- Application of Bayesian approach to numerical methods of global and stochastic optimization
- Performance optimizations for scalable implicit RANS calculations with SU2
- On the sensitivity of structural turbulence uncertainty estimates to time and space resolution
- Towards the ultimate conservative difference scheme. V. A second-order sequel to Godunov's method
- Global optimization of stochastic black-box systems via sequential kriging meta-models
- Turbulent stress invariant analysis: Clarification of existing terminology
- Realizability of Reynolds-stress turbulence models
- Turbulence Modeling in the Age of Data
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