Pages that link to "Item:Q6158540"

The following pages link to Evaluation of physics constrained data-driven methods for turbulence model uncertainty quantification (Q6158540):

Displaying 7 items.

• Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach (Q525932) (← links)
• Rigorous statistical bounds in uncertainty quantification for one-layer turbulent geophysical flows (Q1631293) (← links)
• Approach for uncertainty of turbulence modeling based on data assimilation technique (Q2015965) (← links)
• A confidence-based aerospace design approach robust to structural turbulence closure uncertainty (Q2084092) (← links)
• Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks (Q2214626) (← links)
• A framework to develop data-driven turbulence models for flows with organised unsteadiness (Q2214628) (← links)
• Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence (Q2222797) (← links)