Data driven turbulence modelling

RANS simulation are one of the most used tools for aerodynamic analysis. The advantage of RANS simulations is the reduced computational cost compared to other methods such as LES or DNS. This is because by solving the RANS equations one only solves for the mean flow. However, this reduction in computational cost comes at the price of uncertainty...

Frozen-RANS Turbulence Model Corrections for Wind Turbine Wakes in Stable, Neutral and Unstable Atmospheric Boundary Layers

Computational Fluid Dynamics based on RANS models remain the standard but suffer from high errors in complex flows. In particular, turbulent kinetic energy is over-produced in high strain rate regions, such as the near wake of wind turbine flows. Data-driven turbulence modelling methods aim to derive novel turbulence models with lower...

Numerical Investigation of the Influence of Ground Effect on the FV Aircraft: Influence of Ground Effect on the Flying V Aircraft

In order to meet the growing market demands of quieter, more aerodynamically efficient aircrafts, manufacturers constantly strive to innovate and optimize their designs. Over the years however, the extent of innovation related to the conventional 'tubular fuselage' configurations have somewhat reached a stalemate as the gains obtained have only...

Data-Driven Turbulence Modeling: Discovering Turbulence Models using Sparse Symbolic Regression

Computational Fluid Dynamics (CFD) is the main tool to use in industry and engineering problems including turbulent flows. Turbulence modeling relies on solving the Navier-Stokes equations. Solving these equations directly takes a lot of time and computational power. More affordable methods solve the Reynolds Averaged Navier-Stokes (RANS)...