A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling
From MaRDI portal
Publication:822137
DOI10.1016/j.apm.2020.07.056zbMath1481.76128OpenAlexW2921910744MaRDI QIDQ822137
Francesco Montomoli, Richard Ahlfeld, Audrey Gaymann, Laurens J. A. Voet, Sylvain Laizet
Publication date: 21 September 2021
Published in: Applied Mathematical Modelling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.apm.2020.07.056
direct numerical simulationuncertainty quantificationGaussian CoKrigingnon-intrusive hybrid methodsReynolds-averaged Navier-Stokes simulation
Related Items (1)
Uses Software
Cites Work
- Flow over periodic hills -- numerical and experimental study in a wide range of Reynolds numbers
- Development of DDES and IDDES formulations for the \(k\)-\(\omega \) shear stress transport model
- Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
- SAMBA: sparse approximation of moment-based arbitrary polynomial chaos
- High-order compact schemes for incompressible flows: a simple and efficient method with quasi-spectral accuracy
- Compact finite difference schemes with spectral-like resolution
- Does the choice of the forcing term affect flow statistics in DNS of turbulent channel flow?
- A machine learning approach for efficient uncertainty quantification using multiscale methods
- Flows over periodic hills of parameterized geometries: a dataset for data-driven turbulence modeling from direct simulations
- An efficient multifidelity \(\ell_1\)-minimization method for sparse polynomial chaos
- Recent advances on the numerical modelling of turbulent flows
- Intrusive uncertainty quantification for hyperbolic-elliptic systems governing two-phase flow in heterogeneous porous media
- Multi-fidelity non-intrusive polynomial chaos based on regression
- Incompact3d: A powerful tool to tackle turbulence problems with up to O(105) computational cores
- Multi-fidelity optimization via surrogate modelling
- Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics
- DIRECT NUMERICAL SIMULATION: A Tool in Turbulence Research
- Turbulence Modeling in the Age of Data
- Large Eddy Simulation for Incompressible Flows
This page was built for publication: A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling
