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Detached Eddy Simulations of an Airfoil in Turbulent Inflow

Detached Eddy Simulations of an Airfoil in Turbulent Inflow. Lasse Gilling , Aalborg University, Denmark Niels N. Sørensen , Nat. Lab. Sustainable Energy, Risø/DTU, Denmark Lars Davidson , Chalmers University of Technology, Sweden lg@civil.aau.dk. Agenda. Introduction Computational Setup

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Detached Eddy Simulations of an Airfoil in Turbulent Inflow

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  1. Detached Eddy Simulations of an Airfoil in Turbulent Inflow Lasse Gilling, Aalborg University, Denmark Niels N. Sørensen, Nat. Lab. Sustainable Energy, Risø/DTU, Denmark Lars Davidson, Chalmers University of Technology, Sweden lg@civil.aau.dk

  2. Agenda • Introduction • Computational Setup • Numerical Methods • Inflow Boundary Condition • Results and Discussion • Conclusions Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  3. Introduction • The most common approach to DES of airfoils is to use a mesh like this • Coarse grid far from the airfoil • Fine grid close the airfoil • Laminar inflow with low eddy viscosity • Wind turbines operate close to the ground and are subjected to high levels of turbulence • This work investigates the importance of resolving the inflow turbulence Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  4. Computational Setup Inlet Periodicity Symmetry • Geometry like the wind tunnel • NACA 0015 airfoil • Re=1.6×106 • 21 million cells • Extruded 2D mesh • O-mesh close to the airfoil • Cartesian cells everwhere else • The cells are stretched prior to the outlet • Here every 8th cell is shown Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  5. O-mesh Close to the Airfoil 384×64 cells in O-mesh - 128 cells in spanwise direction Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  6. Cell Sizes • Close to the wall • Cell size in wall units is shown in the figure • Non-constant friction velocity • In the Cartesian part • Δx ≈ 1.4×10-2 c • Δy ≈ 1.6×10-2 c • Δz ≈ 1.2×10-2 c Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  7. Numerical Methods • EllipSys3D • Developed by J. Michelsen and N. Sørensen from DTU and Risø • Incompressible Navier-Stokes equations • Finite volume (cell-centered) • Structured, multi-block grid • Rhie/Chow interpolation • PISO algorithm • Detached eddy simulations with the k-ω SST subgrid turbulence model • Momentum equations are solved with 4th order central difference scheme • 2nd order accurate dual time stepping algorithm Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  8. Inflow Boundary Condition • Fluctuating velocity field is used for inflow boundary condition • Synthetic inflow turbulence is created by the method of Mann • All three velocity components • Components are correlated • Velocity field is divergence free Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  9. Precursor Simulation • Random phases and incorrect statistical moments of third and higher order • The synthetic turbulence is run through a precursor simulation to • Let the flow solver correct random phases and incorrect higher order moments • Let the turbulence adopt to the grid and the numerical method Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  10. Spatial Decay of Homogenous Turbulence • Spatial decay is studied • Test numerical method • Test synthetic turbulence

  11. Spatial Decay of Isotropic Turbulence The three curves should have the same slope as the emperical line Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  12. Results and Discussion: Lift and Drag 1.5 2D RANS DES, TI=0.0% 0.3 DES, TI=0.5% DES, TI=2.0% Measurements 0.25 1 0.2 D L C C 0.15 0.5 0.1 2D RANS DES, TI=0.0% DES, TI=0.5% 0.05 DES, TI=2.0% Measurements 0 0 0 2 4 6 8 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 Angle of attack [deg] Angle of attack [deg] • Flow is sensitive to turbulence • DES with no inflow turbulence predicts stall too late • DES with 0.5% turbulence intensity (TI) gives good agreement before stall • DES with 2.0% TI gives poor results for low AOA but better after stall • 2D RANS is good for low AOA, but fails to predict stall • Experiment: ~0.1% turbulence intensity Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  13. Surface Pressure • Good agreement • Low TI best for low AOA • High TI best for high AOA • Flow very sensitive at 16° AOA AOA=14° AOA=18° AOA=16° Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  14. Skin Friction AOA=14° AOA=18° AOA=16° • For low AOA: • Increased TI moves separation point upstream • For high AOA: • Increased TI moves separation point downstream Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  15. Force History • AOA is 16° – close to stall • Required simulation time depends on the TI • Low TI • Long flow development time • Shows large, slow oscillations • High TI • Short flow development time • Only small, fast oscilations Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  16. Flow Visualization – Low Turbulence • TI is 0.1% and AOA is 16° • Surface limited streamlines and iso-vorticity • Large separation gives low lift and vice versa • Very unsteady, large spanwise variations • Modeling full width of tunnel is required Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  17. Flow Visualization – High Turbulence • TI is 2.0% and AOA is 16° • Surface limited streamlines and iso-vorticity • Much smaller variations in time and spanwise direction • More steady lift Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  18. Averaged Turbulence Intensity • AOA is 12° and TI is 0.5% • Leading edge is located at x/c=0 • Only little decay upstream of the airfoil • Turbulence is generated in the separation bubble and the first part of the wake • Larger decay in stretched part of the grid (for x/c>6) Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  19. Eddy Viscosity • Eddy viscosity normalized by the molecular viscosity • AOA is 12° and TI is 0.5% • High eddy viscosity in the wake and separated region • Eddy viscosity far from the airfoil is constant Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  20. Subgrid Kinetic Energy • Subgrid kinetic energy normalized by the mean velocity squared • AOA is 12° and TI is 0.5% • High subgrid kinetic energy close to the wall • Far from the airfoil is constant and low • Intermediate values in the wake Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  21. Resolved Kinetic Energy • Resolved kinetic energy normalized by the mean velocity squared • AOA is 12° and TI is 0.5% • High resolved kinetic energy in the wake • Far from the airfoil is is constant with a value corresponding to the intensity of the resolved turbulence Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  22. Conclusions • Computed lift and drag depends on the resolved turbulence intensity • Stall is predicted best with TI similar to the one in the experiment • Low AOA: Increased turbulence moves separation point upstream • High AOA: Increased turbulence moves separation point downstream • Best agreement with measurements is obtained • Low AOA: Low turbulence intensity • High AOA: High turbulence intensity Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  23. Future Plans • Implement an actuator disc approach of imposing the turbulence • Turbulence can be imposed immediately upstream of the airfoil • Save mesh points • Investigate the influence of the turbulence length scale Introduction – Computational Setup – Numerical Methods – Inflow Boundary Condition – Results and Discussion – Conclusions

  24. Detached Eddy Simulations of an Airfoil in Turbulent Inflow Lasse Gilling, Aalborg University, Denmark Niels N. Sørensen, Nat. Lab. Sustainable Energy, Risø/DTU, Denmark Lars Davidson, Chalmers University of Technology, Sweden lg@civil.aau.dk

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