2D unsteady computations with deformation and adaptation for COSDYNA Tony Gardner DLR AS-HK

1. 2D unsteady computations with deformation and adaptation for COSDYNATony Gardner DLR AS-HK

2. Summary • Overview of project COSDYNA • Computational geometry • TAU deformation module • Adaptation scheme • Example computations and initial results • Conclusion

3. Show Video 1 (Example of method)

4. HighPerFlex • DLR internal HighPerformance Flexible Aircraft project (HighPerFlex) 2003-2006 • LAWIA – (Last- und Widerstandsabminderung) • Load and drag reduction on a full A340 model by the steady CFD investigation of TED settings on an aeroelastically coupled aircraft. • COSDYNA – (Control surface dynamics) • Numerical and experimental investigation of unsteady profile and TED oscillations • JENIFA – (Jet engine interference in flutter analysis) • Experimental and numerical work to compliment the DLR-ONERA project WIONA (wing with oscillating nacelle)

5. COSDYNA unsteady computations • To compute unsteady coefficients for comparison with TWG experiments in October 2006 • TWG experiments will be performed with a 2D VC-Opt airfoil in the adaptive test section. Forced oscillations of flap and airfoil can be programmed or the airfoil can swing freely. • Computations must be at least partially performed beforehand due to time constraints. • Computations must include flap and airfoil movement. • Optimally, computations will not include gap flow • Computations include cases with strong shocks, and thus will optimally allow adaptation

6. 2D VC-Opt airfoil in TWG

7. Geometry • VC-Opt, length 300mm • Design Mach =0.775 • With 25% flap (gapless) deployed by grid deformation • Re=2 million • 2D CENTAUR grid • Farfield at r=50 chords (needs farfield vortex correction) • Surface points at 2mm spacing • 28 structured sublayers (no cell chopping) • Built for y+=1 • Raw grid has 50,000 points before 2D reduction

8. Flap movement • Chimera • Requires a gap between body and flap (non-physical) • Gapless using automatic hole cutting is in development • Deformation • Can perform gapless movement • Requires definition of the new surface position • Handling the hinge requires care • Simplifies grid generation

9. TAU Deformation • Tau deformation takes a surface deformation and deforms the volume grid to enclose this new surface • The grid points and numbering (GID) are preserved in the new grid, changing only the grid point positions. Solutions in TAU use GID. • A deformation can be expressed as (x, y, z), (x, y, z) or as a 3D, algebraic test deformation (z=C{y-y0}2) • TAU version 2005.1.1 • Not explicitly 2D (accumulated machine precision errors) • Adaptation level information destroyed on reading of grid • No 2D algebraic test deformation • TAU version 2006.1.0 • Grid quality problems with incremental deformations • No 2D algebraic test deformation

10. TAU version • Based on 2005.1.1 with 2D adaptation patch • Added 2D deformation (Gerhold) • Added adaptation level loading (Gerhold) • Added 2D linear algebraic deformation • Deforming as: z=C(x-x0) • Using shell script in serial • Python was attempted, but I couldn’t get the scripts working. • Due to development status and lack of documentation? • Writing a solution each time step means that saved IO in Python is not as significant as it might be in other cases.

11. Script execution in serial (Data passing as disk write) Steady starting solution (20 mins) Unsteady computation (2-3 days) Deformation Unsteady solver Steady solver Adaptation Adaptation Deformation Steady solver Unsteady solver

12. Adaptation method • “Default rules” with the following additions: • Restrictions: • Maximum point number (150,000) • Minimum edge length (1mm) • Cut-out box to reduce cells in the wake • Adaptation type is “both” • Method: • Add cells to “maximum point number” in the steady calculation • Adapt after every time step • “Percentage of new points” is 20% to avoid a reduction in the number of points over time

13. Example Grid 1/4

14. Example Grid 2/4

15. Example Grid 3/4

16. Example Grid 4/4

17. Time stepping study • Flap movement (): 0.0  1.0 degrees • Pitching amplitude (): 0.0  0.2 degrees • Reduced frequency (): 0.40 / 0.80 • Ma: 0.80 • Steps/period: 25, 50, 100, 200

19. Grid refinement study • Very difficult to undertake, even in 2D • Currently testing against a number of static, unrefined grids • Problems with large grid sizes of static grids • Refinement cases where surface grid size and tetrahedral stretching were reduced did not converge, up to 300000 cells. • Currently trying other refinement methods.

22. Unsteady solver settings • 100 inner iterations/timestep • 200 timesteps/period • 6 periods for a computation • SAE turbulence model • Central solver by Backward Euler • Multigrid scheme 5w • CFL number fine = 10 • CFL number coarse = 20

23. Show Videos 2 and 3 • Ma=0.8 • Re=2 million •  =0.15 (~20 Hz) • Video2: Body oscillation only.  = 0.0  0.2 degrees • Video3: Flap oscillation only.  = 0.0  1.0 degrees

24. First results

25. Conclusions and further work • Under special conditions, 2D unsteady computations with adaptation and deformation appear to work. • Verification of the results with experiment still needs to be undertaken. • Grid refinement studies are still a problem • A similar approach could be undertaken using Python scripting.