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
Slide 3
Atmospheric pressure plasmas have a broad range of industrial
applications AerospaceEnergy Plasma Processing Plasma Medicine
Slide 4
Applications Why does one need modeling?
Slide 5
Aerospace: DBDs Applications . rest Why does one need
modeling?
Slide 6
Aerospace: DBDs Applications . rest Power Supplygeometry,
materials, Why does one need modeling?
Slide 7
Aerospace: DBDs Applications . rest Power Supplygeometry,
materials, 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? AC, DC, RF..? Why does one need
modeling?
Slide 8
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 Complete,
comprehensive plasma model requires:
Slide 9
Ionization Recombination Attachment Detachment Photoionization
Detailed air chemistry? Excitation? Fast heating? The model needs
to include complex plasma processes
Slide 10
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 Plasma
model requirements:
Slide 11
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 10 6 -10 7 grid points for
just 2D The model needs to resolve plasma/system spatial
scales
Slide 12
Time scales: Electron drift velocity ~ 10 6 m/s picosecond time
step due to CFL The cycle of device operation ~ ms millisecond time
interval should be computed 10 9 time points Need to use
state-of-the-art numerical techniques The model needs to resolve
plasma/system time scales
Slide 13
Drift-diffusion approximation Easy to implement Best for
relatively low E/n High pressures 2-moment model Drift-diffusion +
electron energy equation Low to moderate E/n High pressures
5-moment model Momentum and energy equations Low to moderate E/n
Low to high pressures Kinetic approach Particle in Cell Detailed
plasma description non-local effects Low to high E/n Low to high
pressures Model Complexity Code Performance The model needs both to
solve appropriate equations and to be computationally
efficient
Slide 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)
Slide 15
Electrons Positive ions Charge photoionization potential
Electric field What physics are we interested in? Quasi-neutral
bodySheathConductive channelStrong Efield near head
Slide 16
0.3 ns2.1 ns3.0 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 PIC model provides correct electric potential
evolution during streamer propagation X, m Y, m
Slide 17
High density of electrons in streamer body Low density of
electrons ahead of streamer head Almost no electrons anywhere else
PIC model provides correct electron distribution within streamer
body Y, m X, m
Slide 18
Electrons are combined in the region of high electron density
(streamer body) Electrons are not combined (accurate resolution)
around streamer head Concept of variable-weight particles allows
accurate and efficient streamer simulation in VORPAL Y, m Particle
weight X, m
Slide 19
Set 1 Grid size: 0.5x0.5 microns Threshold for combining
macroparticles is 3 Set 2 Grid size: 0.5x0.5 microns Threshold for
combining macroparticles is 10 Perform validation study of the
particle combining algorithm
Slide 20
3.3 ns Changes in threshold for combining macroparticles do not
change results Efield is lower than in fluid modeling Horizontal
component of Efield for the developed streamer is the same for both
cases 2D Ex, V/m Set 1Set 2 1D Ex, V/m
Slide 21
x z 3D DBD simulation - ElectronsZ-component of Efield, top
view z x VORPAL can perform 3D DBD simulations and resolve 3D
filamentary structure
Slide 22
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 Why can
PIC be efficient at high pressures? When to use PIC: Validate fluid
models Resolve physics which fluid codes cannot handle
Slide 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
Slide 24
Positive ions potential Electric field 20*log(Np) VORPAL can
reproduce major physical phenomena for streamer propagation Plasma
is in streamer form Potential is quasi-uniform within streamer body
Electric field is strong at the streamer head
Slide 25
DBD Property Experimental Results (3kV, 5ns) (Princeton)
Numerical Results (3kV, 4ns) Qualitative Comparison Result Plasma
length~ 2 mm~ 0.5 mmFair agreement Plasma thickness 150-200 microns
100 microns for fluid approach 250 microns for kinetic approach
Good agreement Consumed Energy per plasma volume ~20 kJ/m 3 ~18
kJ/m 3 Excellent agreement VORPAL is quantitatively validated
against experimental data
Slide 26
1)Obtain spatial and temporal distribution of force and heating
terms from VORPAL 2)Insert them as RHS into Navier-Stokes equations
3)Study DBD-flow interaction VORPAL output can later be coupled
with CFD tools airfoil Example of flow separation simulation in
Nautilus, Tech-Xs CFD/MHD code on unstructured meshes
Slide 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?
Slide 28
Proposed experimental setup at Princeton (M=3 wind tunnel)
Slide 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
Slide 30
Fluid code Nautilus General purpose fluid plasma modeling code
Supports shock capturing methods for MHD, Hall MHD, Two-Fluid
plasma, Navier Stokes and Maxwells equations Bodyfitted and
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
Slide 31
Models for SWBLI (similar to Shneiders 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
Slide 32
Numerical Grid
Slide 33
Grid resolution study / no plasma case Coarse Medium Fine
Schlieren ImageHorizontal component of velocity
Slide 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: ~ - 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
Slide 35
DBD placement
Slide 36
Simulation cases 1MHz pulses:
Slide 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
Slide 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
Slide 39
Observations: Shock wave moves upstream (similar observation to
Samimys experiments)variables Additional mixing in boundary layer
Main influence by upstream DBD - good placement is at the free flow
/ 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
Slide 40
Acknowledgements: NASA Glenn Research Center (Dr. David Ashpis)
NASA Langley Research Center (Dr. Fang-Jenq Chen) Wright-Patterson
AFRL (Dr. Jon Poggie)