Aerospace Plasmas

1. Aerospace Plasmas Alexandre Likhanskii, Kris Beckwith Tech-X Corporation Tech-X Workshop / ICOPS 2012, Edinburgh, UK 8-12 July, 2012

2. DBD Background • Stall control for up to M=0.4 using AC driven DBDs • Stall control for transonic flow using ns-pulse driven DBDs • Bow shock control using ns-pulse driven DBDs • SWBLI control using LAFPA

3. Atmospheric pressure plasmas have a broad range of industrial applications Aerospace Energy Plasma Processing Plasma Medicine

4. Why does one need modeling? Applications

5. Why does one need modeling? Applications Aerospace: DBDs …. rest

6. Why does one need modeling? Applications Aerospace: DBDs …. rest Power Supply geometry, materials, …

7. Why does one need modeling? Applications Aerospace: DBDs …. rest Power Supply geometry, materials, … • AC, DC, RF..? • Pulser • What is the optimum pulse duration? • What is the rise time? • What is the repetition rate? • What is the power consumption? • How heavy is it?

8. Complete, comprehensive plasma model requires: • Solve for charged species motion coupled with Poisson Solver • Include all relevant plasma processes • Resolve all relevant spatial and time scales • Use appropriate physical model for plasma description at particular conditions • Couple with CFD code

9. The model needs to include complex plasma processes • Ionization • Recombination • Attachment • Detachment • Photoionization • Detailed air chemistry? • Excitation? • Fast heating?

10. Plasma model requirements: • Solve for charged species motion coupled with Poisson Solver • Include all relevant plasma processes • Resolve all relevant spatial and time scales • Use appropriate physical model for plasma description at particular conditions • Couple with CFD code

11. The model needs to resolve plasma/system spatial scales • Spatial scales: • Plasma sheath size is ~ 10 microns micron grid size • Plasma length is several millimeters millimeter numerical domain for plasma generation • Surface charge accumulation centimeter numerical domain for surface charging • 106-107 grid points for just 2D

12. The model needs to resolve plasma/system time scales • Time scales: • Electron drift velocity ~ 106 m/s picosecond time step due to CFL • The cycle of device operation ~ ms millisecond time interval should be computed • 109 time points • Need to use state-of-the-art numerical techniques

13. The model needs both to solve appropriate equations and to be computationally efficient Model Complexity Code Performance

14. Options / Approaches • Non-uniform (unnecessary refinement) or adaptive grids (difficult to make parallel) • Variable time steps (validate physical assumptions) • Implicit methods (stable, but require validation of grid size and time step choices) • High-performance clusters (additional investments)

15. What physics are we interested in? photoionization Electrons Positive ions potential Electric field Charge Quasi-neutral body Sheath Conductive channel Strong Efield near head

16. PIC model provides correct electric potential evolution during streamer propagation Y, m X, m X, m X, m 0.3 ns 2.1 ns 3.0 ns • Electric potential evolution represents classical streamer propagation -> conductive plasma carries the potential of exposed electrode • Streamer is higher and thicker than in the fluid models

17. PIC model provides correct electron distribution within streamer body Y, m X, m • High density of electrons in streamer body • Low density of electrons ahead of streamer head • Almost no electrons anywhere else

18. Concept of variable-weight particles allows accurate and efficient streamer simulation in VORPAL Y, m Particle weight X, m • Electrons are combined in the region of high electron density (streamer body) • Electrons are not combined (accurate resolution) around streamer head

19. Perform validation study of the particle combining algorithm

20. Horizontal component of Efield for the developed streamer is the same for both cases Set 1 Set 2 2D Ex, V/m 1D Ex, V/m 3.3 ns 3.3 ns • Changes in threshold for combining macroparticles do not change results • Efield is lower than in fluid modeling

21. VORPAL can perform 3D DBD simulations and resolve 3D filamentary structure 3D DBD simulation - Electrons Z-component of Efield, top view z z x x

22. Why can PIC be efficient at high pressures? • Efficient in parallel • Streamer resolution • Using particle combination during breakdown and splitting during plasma decay avoid over- and under-resolution • Simulations from first principles, detailed physics • Fluid models are generally more efficient • When to use PIC: • Validate fluid models • Resolve physics which fluid codes cannot handle

23. Fluid DBD model in Vorpal • Time-dependent plasma dynamics in drift-diffusion approximation coupled with 2D Poisson solver for electric potential distribution • Air: neutrals, electrons, positive and negative ions • Electron temperature, ionization, recombination, attachment, detachment and transport parameters: functions of E/N • Proper boundary conditions (incl. charge build-up on dielectric surface, surface recombination and secondary electron emission) • Subnanosecond time scales and micron geometrical scales are properly resolved for accurate plasma modeling • Background plasma density • Plasma model provides force and • heating terms for Navier-Stokes solver

24. VORPAL can reproduce major physical phenomena for streamer propagation 20*log(Np) Positive ions potential • Plasma is in streamer form • Potential is quasi-uniform within streamer body • Electric field is strong at the streamer head Electric field

25. VORPAL is quantitatively validated against experimental data

26. VORPAL output can later be coupled with CFD tools Obtain spatial and temporal distribution of force and heating terms from VORPAL Insert them as RHS into Navier-Stokes equations Study DBD-flow interaction airfoil Example of flow separation simulation in Nautilus, Tech-X’s CFD/MHD code on unstructured meshes

27. Application of DBDs to Shock-Wave Boundary Layer Interaction problem • Control using snow plow arcs by momentum transfer (Princeton) • Control using LAFPLA by heat deposition (Ohio State) Can we control SWBLI using pulsed DBD?

28. Proposed experimental setup at Princeton(M=3 wind tunnel)

29. What can modeling do? • VORPAL has an experimentally validated capability to compute heat deposition by high-V ns pulses • Need an accurate CFD tool to compute SWBLI

30. Fluid code Nautilus • General purpose fluid plasma modeling code • Supports shock capturing methods for MHD, Hall MHD, Two-Fluid plasma, Navier Stokes and Maxwell’s equations • Bodyfittedand unstructured grids in 1, 2 and 3 dimensions • Ability to model the plasma device as part of a circuit • Massively parallel and has been run on up to 4000 processors on NERSC facilities. • Recent applications of Nautilus have included modeling merging plasma jets, laboratory accretion disk experiments, weakly ionized hypersonic flow modeling, magnetic nozzles and capillary discharges. • Multi-platform tool: Windows, Mac and Linux

31. Models for SWBLI(similar to Shneider’s model) • Dimensionally unsplit MUSCL-Hancock integrator (``Van-Leer'') using second order spatial reconstruction in the primitive variables • Prandtl-Boussinesq turbulence model • Super time stepping method to use hyperbolic time step for CFD simulations • Compute steady-state solution for SWBLI without DBD • Obtain gas parameters in BL for DBD model in Vorpal • Compute pulsed DBD heat deposition in Vorpal • Use Vorpal data as a heat source for Nautilus CFD simulations

32. Numerical Grid

33. Grid resolution study / no plasma case Schlieren Image Horizontal component of velocity Coarse Medium Fine

34. DBD simulation for the boundary layer • Applied Votage :7kV, 5ns pulse • Numerical domain: 2cm x 1mm • Grid size: 2x2 microns • Running on 64 core • Typical run time: ~ ½ - 1 day • Output: streamer dimensions: ~1cm x 200 microns, propagating ~500 microns above the surface • Output: temporal and spatial distribution of instant and integrated energy release • Output: total energy (E*J) release = 8mJ/m

35. DBD placement

36. Simulation cases – 1MHz pulses:

37. Schlieren: SWBLI control with pulsed DBDs Case A Plasma OFF Baseline Case B Plasma ON Instantaneous heat deposition Case C Plasma ON Realistic heat deposition

38. Vx: SWBLI control with pulsed DBDs Case A Plasma OFF Baseline Case B Plasma ON Instantaneous heat deposition Case C Plasma ON Realistic heat deposition

39. Observations: • Shock wave moves upstream (similar observation to Samimy’s experiments)variables • Additional mixing in boundary layer • Main influence by upstream DBD - good placement is at the freeflow / boundary layer interface to induce mixing • DBDs deep inside BL do almost nothing, but heat the BL • Overall, DBD can effect SWBLI but more optimization studies are necessary - mainly DBD placement and pulse repetition rate

40. Acknowledgements: • NASA Glenn Research Center (Dr. David Ashpis) • NASA Langley Research Center (Dr. Fang-Jenq Chen) • Wright-Patterson AFRL (Dr. Jon Poggie)