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physics.flu-dyn2022
Machine learning based uncertainty quantification of turbulence model for airfoils
Minghan Chu, Weicheng Qian
Reynolds-averaged Navier-Stokes (RANS)-based transition modeling is widely used in aerospace applications but suffers inaccuracies due to the Boussinesq turbulent viscosity hypothe…
physics.flu-dyn2022★ 1 cited
Model form uncertainty quantification of Reynolds-averaged Navier-Stokes modeling of flows over a SD7003 airfoil
Minghan Chu, Xiaohua Wu, David E. Rival
It is well known that the Boussinesq turbulent viscosity hypothesis can yield inaccurate predictions when complex f low features are involved, e.g. laminar-turbulent transition. Th…
physics.flu-dyn2022★ 9 cited
Quantification of Reynolds-averaged-Navier-Stokes model form uncertainty in transitional boundary layer and airfoil flows
Minghan Chu, Xiaohua Wu, David E. Rival
It is well known that Boussinesq turbulent-viscosity hypothesis can introduce uncertainty in predictions for complex flow features such as separation, reattachment, and laminar-tur…