effect of roughness on a turbulent boundary layer in hypersonic flow

1. Effect of Roughness on a Turbulent Boundary Layer in Hypersonic Flow Dipankar Sahoo, Marco Schultze1 and Alexander J. Smits Princeton University and 1University of Stuttgart Supported by NASA Cooperative Agreement NNX08AB46A 39th AIAA Fluid Dynamics Conference June 22-25, 2009, San Antonio, TX

3. Background For flows Mach > 5, the general features of the mean flow behavior are reasonably well known, with a focus on surface data -- pressure, heat transfer, skin friction (Roy and Blottner, 2006) The mean flow, when transformed according to Van Driest, appears to follow the incompressible scaling and independent of Mach number.

4. Background Accurate and reliable turbulence measurements are difficult to make in supersonic flow; the difficulties are greater at higher Mach numbers (Smits & Dussauge, 1995) Very few turbulence measurements exist for Mach > 5. Examples include: Owen & Horstman (1972) Constant temperature, two-component hot-wire measurements, including auto and cross-correlations, at Mach 7.0, Re? = 8500 Berg (1977) Constant current, one component hot-wire measurements, at Mach 6.0, Re? = 14000 - 16000 McGinley, Spina & Sheplak (1994) Constant temperature, one component hot-wire measurements at Mach 11, Re? = 6540, 12040 Much of the other hypersonic turbulence measurement work suffered from poor frequency response and/or suspect calibrations (McGinley, Spina & Sheplak, 1994)

5. Mach 7.2 (Owen et al., 1975) Hot-wires measure (?u)� Use Strong Reynolds Analogy to deduce u� Similarity expected to follow Morkovin, but high Mach number data does not support low Mach number data

6. Effects of roughness Only two sets of relatively complete turbulence data with roughness exist for high speed flow: Berg (1977) and Ekoto et al. (2008) Berg (1977): Mach 6, near adiabatic flow, square bar roughness (k+ = 33.8, ?/k = 25) Equivalent sand grain roughness was half the value in subsonic investigations Effective origin was below the crest of roughness element Ekoto (2008) Mach 2.86, adiabatic flow, diamond mesh and square block roughness (k+ = 100, ?/k = 15) Diamond roughness caused local distortions which affected mean and turbulent flow. The effect of square roughness was much less significant. For weak local distortions, inner-scaling captures the effect of roughness on turbulence without Morkovin�s scaling

7. Research objectives To improve our understanding of the effects of roughness on hypersonic turbulent boundary layers Approach: Obtain experimental data in hypersonic rough turbulent boundary layers (Mach 7.2) at DNS accessible Reynolds numbers (3260 < Re? < 4450) Smooth plate Two types of roughness: 3D Diamond mesh and 2-D square bars Use Particle Image Velocimetry (PIV) to obtain velocity directly Compare results with DNS (Pino Martin at Princeton)

8. Mach 8 facility Stagnation Temperature � up to 875K Stagnation Pressure � up to 1500 psia Useful Run time: 90-120 s

9. Mach 8 facility air supply 4 storage tanks (3000 psi) 8 existing air cooled Ingersoll Rand compressors Automated Provide enough air to run every second day 2 water cooled Worthington compressors Refurbished and added to the main supply line Manual control Provide enough air to run every 6 Hrs.

10. Test model 2. 4 mm high tripwire Painted black to reduce laser reflections: surface roughness < 2?m Region of measurement: 380 mm from LE FOV (Field of view) = 22 mm x 22 mm

12. Hot-wire anemometry will not give accurate results at high stagnation temperatures Use Particle Image Velocimetry (PIV) for velocity field Statistical data Structural data New Wave � Gemini PIV dual head laser 532 nm./100 mJ per pulse. Jitter - � 0.5 ns ?t � 0.4 ?s High speed PCO Cooke camera Pixel resolution - 1600 x 1200 Short exposure � 500 ns Berkeley box Trigger the laser and camera

13. Challenge for PIV � high flow velocity, low density

14. PIV - seeding Seeding particles TiO2 Particles Manufacturer- specified diameter 50 nm Effective diameter 400 nm Particle injection In the settling chamber upstream of the throat Injection through 0.5� tube on centerline Fluidized bed plus cyclonic separator (based on Clemens design) Heating tape on fluidized bed reduces coalescence and improves particle dispersion

15. PIV - experimental set-up

16. PIV images Typical PIV images with diamond mesh and square bar roughness FOV ~ 22 x 22 mm

17. PIV � data analysis Calibrate using precision grid Discard images with unsatisfactory seeding density Shift and rotate images to allow for tunnel movement (< 0.5?) Three-step adaptive correlation (128 x 128, 64 x 64, 32x32 with 50% overlap) Apply consistency filter (minimum 3 particles) Apply velocity range validation filter Discard data within 0.3mm of edge of each image Non-dimensionalize velocity data before summing over multiple runs

18. Flow parameters

19. Smooth wall mean flow

20. Smooth wall turbulence

25. Rough wall mean flow

26. Rough wall wake similarity

27. Rough wall turbulence

28. Conclusions Mean flow comparisons were independent of Mach number in transformed coordinates Turbulence intensities showed strong effect of compressibility Mean velocity profiles for rough wall showed expected shift below log law Transitional effect may have caused the decrease in wake parameter Strong damping was observed in case of streamwise and wall normal velocity fluctuations

29. Need to increase the particle flow rate by increasing the size of the pipe in the seeding system Need to perform further experiments with smaller roughness elements Need to obtain a larger experimental database to establish the observations so far Future Work

30. Acknowledgements NASA Cooperative Agreement NNX08AB46A Program Manager: Catherine McGinley Robert Bogart for assisting in setting up the experiments and running the tunnel. QUESTIONS?

31. Boundary layer parameters