computational plasma physics

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TU/e Computational Plasma Physics To “cage” the cosmic medium: plasma t an overview of all the various Methods, Models, and To Get controle over its diversity Introduce young researchers/modellers nstruct a modeling platform for the industry Aims

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Computational Plasma Physics. Aims. To “cage” the cosmic medium: plasma. Get controle over its diversity. Get an overview of all the various Methods, Models, and Tools. Construct a modeling platform for the industry. Introduce young researchers/modellers. Has to be organized. - PowerPoint PPT Presentation

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Page 1: Computational Plasma Physics

TU/e

Computational Plasma Physics

To “cage” the cosmic medium: plasma

Get an overview of all the various Methods, Models, and Tools

Get controle over its diversity

Introduce young researchers/modellers

Construct a modeling platform for the industry

Aims

Page 2: Computational Plasma Physics

TU/e

Structure of the course

Lectures Joost van der Mullen (Tue) Wim Goedheer (FOM Nieuwegein)Annemie Bogaerts (Uni Antwerp)Ute Ebert (CWI)

Practicum Bart HartgersWouter brokBart Broks

Examination: Projects

Has to be organized

Page 3: Computational Plasma Physics

TU/e

Interdiscipline

MathNum SoftWArch

PlasmaPhysics

Page 4: Computational Plasma Physics

TU/e

Metal Halide Lamp

10 mBar NaI and CeI3 in 10 bar Hg

Gravitation inducedSegregation

Page 5: Computational Plasma Physics

TU/e

The Philips QL lamp• Buffer argon (33 Pa)• Light Mercury (1 Pa)• Inductively coupled• Power 85 W

Electrodeless lamp: long life time

Page 6: Computational Plasma Physics

TU/e

GEC RF discharge

Page 7: Computational Plasma Physics

TU/e

Spectrochemical Plasma Sources

ICP

induction coil

active zone (AZ)

15l/min outer flow

intermediate flow

central channel (CC)

central flow

•100 MHz•100 kHz;

350 sccm He

transformer

60 mm

CCP

4 mm i.d.

18 mm i.d.

Open air•0.3 - 2 kW•10- 50 W

•Argon•Helium

Page 8: Computational Plasma Physics

TU/e

Microwave Plasma Torch (MPT)

Frequency 2.45 GHz

Power 100W

Argon flushing intoThe open air

Page 9: Computational Plasma Physics

TU/e

Booming Plasma Technology

Interest increasing rapidly

Material sciences (sputter) deposition CD, IC, DVD, nanotubes, solar-cells,

Environmental gas-cleaning, ozon production, waste destruction

Light Lamps, Lasers, Displays: Visible + EUV

Propulsion Laser Wake field, Thrusters

Etc. Etc

Page 10: Computational Plasma Physics

TU/e

Components

Material Particles Neutral Charged

Dust

Fields

Photons

Note the various interactions

Continuum or Particle

And/Or ?? “Hybrid”

Page 11: Computational Plasma Physics

TU/e

Plasma Chemistry Volume Particles

Surface Particles + environment

Plasma Propulsion Momentum

Plasma Light Energy

Particles, Momentum, Energy

Page 12: Computational Plasma Physics

TU/e

Ordering

Particles Chemistry m

Momentum Propulsion mv

Energy Conversion 1/2mv2

Page 13: Computational Plasma Physics

TU/e

Energy Coupling; Ordering in frequency

DC Cascaded Arcs Deposition/Lightsources

AC HID/FL lamps Welding/Cutting/light

CC GEC cell etc. Etching/Depo/ SpectrChem

IC QL lamp Licht/ Spectrochemistry

Wave Surfatron Material processing

Laser ProPl Ablation Cutting/ EUV generation

Pulsed DC pHollowCathodeD EUV gen/switchesCorona Disch. Volume cleaning

Page 14: Computational Plasma Physics

TU/e

Momentum

Via E field: Plasma PropulsionSheath: ion accelerationOhms law: electon current

Via p : expansionCascaded Arc

Page 15: Computational Plasma Physics

TU/e

Chemistry; global ordering

Atomic Molecular

Low High pressure

Page 16: Computational Plasma Physics

TU/e

Chemistry; finer ordering

Plasma gas i.e. Hg in a FLamp

Buffergas i.e. Hg in a HID lamp; Ar in a FL

Starting gas Xe in HID lamp

Reduction diffusionEnhencing resistance

electrons, M-ions A-ionsatoms, molecules; Radicals etc.

Final Chemistry

Page 17: Computational Plasma Physics

TU/e

Transport Modes

Fluid mean free paths small mfp << L

Quasi Free Flight mean free paths large mfp > L

Sampling and tracking

Hybride

There are many conditions for which some plasma components behave “fluid-like”whereas others are more “particle-like”

Hybride models have large application fields

Page 18: Computational Plasma Physics

TU/e

Particles

Energy

Particles

Energy

Momentum Momentum

Particles: Plasma Chemistry

Energy: Plasma Light

Momentum: Plasma Propulsion

Page 19: Computational Plasma Physics

TU/e

Fluid models; a flavor

Continuum approach:

Differentiation/Integration possible

Not jumping over neighbour’s garden

Page 20: Computational Plasma Physics

TU/e

Discretizing a Fluid: Control Volumes

Particles

Energy

Momentum

Particles

Energy

Momentum

For any transportablequantity

Source

Transport via boundaries

Page 21: Computational Plasma Physics

TU/e

Examples of transportables

Densities

Momenta in three directions

Mean energy (temperature) of electrons

Mean energy (temperature) of heavies

How many species?

How many species?

As we will see: in many cases energy: 2Tmomentum: Drift DiffusionSpecies depending on equilibrium departure

Page 22: Computational Plasma Physics

TU/e

Nodal Point communicating via Boundaries

Mean properties Nodal Points

Transport at boundaries

Transport Fluxes: Linking CV (or NP’s)

= u -D General structure:

-

Transient

t + = S = Source,

Steady State

DiffusionConvection

Page 23: Computational Plasma Physics

TU/e

Modularity

Thus: The Fluid Eqns: Balance of Particles MomentumEnergy

The Momenta of the Boltzmann Transport Eqn.

Treated all as -equation

Other Example: Poisson: .E = /o

E = -V

Thus no “convection”

= S

= u -D

Page 24: Computational Plasma Physics

TU/e

The Variety

D S

Temperature Heat cond Heat gen

Momentum Viscosity Force

Density Diffusion CreationMoleculesatomsions/electronsetc.

Page 25: Computational Plasma Physics

TU/e

Coupling different -equations

Source of ions 1

Associated with Sink in Energy 2

Page 26: Computational Plasma Physics

TU/e

Advantages of the -approach

The same solution procedure: the same base class

Possible to combine all the s in one big Matrix-vector eqn.

Page 27: Computational Plasma Physics

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MathNumerics: a FlavorSourceless-Diffusion

Rod Tin Tout

Continuumt + = S

0 + T = 0

T = - kT

T = Cst

-T /k =T

T

xTake k = Cst

Page 28: Computational Plasma Physics

TU/e

Discretized

Rod Tin Tout

Continuum

Discretized

1 2 3 4Intuition; T = Cst

T2 = (T1 + T3)/2

2T2 = T1 + T3

Tin -2T1 + T2 = 0 T1 - 2T2 + T3 = 0 T2 - 2T3 + T4 = 0

T3 - 2T4 + Tout = 0

Page 29: Computational Plasma Physics

TU/e

Matrix Representation

- 2 1

1 -2 1

1 -2 1

1 -2

1

2

3

4

1 2 3 4

T1

T2

T3

T4

=

-Tin

0

0

-Tout

M T = bIn matrix:A Sparce MatrixMany zeros

Page 30: Computational Plasma Physics

TU/e

Sourceless-Diffusion in two dimensions

11 – 4 1 1

T5 = (T2 + T4 + T6 + T8 ) /4

NW P E S

Provided k = Cst !!

In general: 4

NB

NB

P

TT

Page 31: Computational Plasma Physics

TU/e

More general S-less Diffusion/Convection

NB NB

NBNBNB

P c

TcTIf k Cst

NB NB

NBNBNB

P c

TcT

*

*

ConvectionDiffusion

Page 32: Computational Plasma Physics

TU/e

Ordering the Sources

S = P - L

L ~ D

Source combination Production and Loss

= S

Large local - value in general leads to large Loss

Source of ionsExample ions: nu+ = P+ - n+D+

Recombination

Page 33: Computational Plasma Physics

TU/e

The number of -equations

How many -equations do we need ??

The number of transportables Depends on the degree of equilibrium departure

Method of disturbed Bilateral Relations dBR

Insight in equilibrium departure global model ne, Te and Th

Page 34: Computational Plasma Physics

TU/e

Particles

Energy

Particles

Energy

Momentum Momentum

Page 35: Computational Plasma Physics

TU/e

Plasma Artist Impression

Input and Output Intermediated by Vivid Internal Activity

Page 36: Computational Plasma Physics

TU/e

Global Structure

Inlet Outlet

Internal Activity

The In/Efflux couple will disturb internal Equilibrium Inlet side will be pushed up; Outlet pushed down

But when do we have equilibrium ???

Page 37: Computational Plasma Physics

TU/e

TE: Collection of Bilateral Relations

TE Equilibrium in (violet) thermal dynamics

DB Equilibrium on each level (each ) for any process-couple along the same route

N f

N b

Page 38: Computational Plasma Physics

TU/e

Disturbance of BR by an Efflux

t = Nt

N b

N f

Equilibrium Condition: t/b << 1 or t b << 1

The escape per balance time must be small

Page 39: Computational Plasma Physics

TU/e

N f

N b

Equilibrium Departure

Non-Equilibrium N f = N b + N t

Equilibrium N eqf = N

eqb y() = y()[1+ (tb)]

y = N/Neq

Page 40: Computational Plasma Physics

TU/e

Emission = Absorption

Planck

The Nature of the Processes; PROPER Balances

Excitation = Deexcitation Boltzmann

Ionization = RecombinSaha

Kinetic Energy ExchangeMaxwell

=1 =+

Page 41: Computational Plasma Physics

TU/e

Nomenclature induced by dBR

TE, LTE, pLTE ??

Any situation aspectsEquilibrium

Non-Equilibrium

Partial Equilibrium

Nature Saha

BoltzmannPlanck

Maxwell

pLSEpLBEpLPEpLME

Proper Balances

Page 42: Computational Plasma Physics

TU/e

Proper versus Improper balances

Forward and corr. Backward

MR and Energy Conservationgive standard relations

Proper

ImproperBackward negligible Assumption: d/dt = 0

Analytical expressions (!?)

Page 43: Computational Plasma Physics

TU/e

Example pLPE

=1 =2

Intense laser irradiates transition:

Proper balance Absorption St.Emission

Look for comparable TE situation

T : exp-E/kT=1 (1) = (2)

h= E

(p) = n(p)/g(p) number density of a state; n(p) = number density of atoms in level pg(p) = number of states in level p

Page 44: Computational Plasma Physics

TU/e

Example pLSE

Groundstate

Ion

state

Ionization flow OutfluxInflux

Approaching continuum:

Equi. restoration rates increase

Look for comparable TE situation

Saha equation ruled by electrons from continuum

s(p) = (ne/2) (n+/g+) [h3/(2mekTe)3/2] exp (Ip/kTe)

Page 45: Computational Plasma Physics

TU/e

The Saha density: mnemonic

s(p) = (ne/2) (n+/g+) [h3/(2mekTe)3/2] exp (Ip/kTe)

s(p) = e + [V(Te) ] exp (Ip/kTe) That is

Number density of bound {e +} pairs in state p: s(p) Equals the density of pairs within V(Te) e + [V(Te) ] Weighted with the Boltzmann factor exp (Ip/kTe)

Ap A+ + e Look at balance

A+ + e bound free pair

Page 46: Computational Plasma Physics

TU/e

The Corona Balance: an improper balance

y() = y()[1+ (tb)B ] with (tb)B

= A/ne K(2,1)

The larger ne the smaller departure

Escape of Photons

Restoring: Proper Boltzmann

b(2) = b(1) exp { -E12/kTe}Tends to

Page 47: Computational Plasma Physics

TU/e

General: Impact Radiation Leak

p

y(p) = y(1)[1+ tb]-1

with

tb = A*(p)/ne K(p,1)

Define: N = A(p)/neK(p)

A(p) p-4.5 K(p) p4

N (p)p-9

Page 48: Computational Plasma Physics

TU/e

I1 0

bp

realdistribution

pLSE

Saha distribution

log(

ele

men

tary

occ

upat

ion

)

Ip

Groundstate

Ion

state

Ionization flow OutfluxInflux

Ion Efflux Effecting the ASDF

pLSE settles for Ip 0

since (t/b)S 0

b = n/ns

Page 49: Computational Plasma Physics

TU/e

If Ambipolar Diffusion Dominates

t = Da/L2

t = n+t = .n+ w+

n+ w+ = -Da .n Diffusion

b(1) = (tb)s = t/ (ns(1) Sion) Cb (A) x 108 Da (neL)-2

Moderate deviations for large ne, large L and small Da

For single ionized ns(1) ~ nen+= ne2

Page 50: Computational Plasma Physics

TU/e

F(E)

E12E

Ion Efflux Effecting the EEDF

= bulk = tail

Page 51: Computational Plasma Physics

TU/e

Deviation form pLME

F(E)

E12E

= bulk = tail

y() = y()(1 + t b)

y()/ y() = (1 + t b)-1

Tt /Tb = y()/ y()

(t b)M = C(A) [n1/ ne] {kTe/E12}2 / lnc

Competition between bound and bulk electronsionization ratio important ne /n1

Tt/Te

Page 52: Computational Plasma Physics

TU/e

Disturbed Bilateral Relation

•To find essential non-equilibrium featuresEfflux Equilibrium restoring Balance

•Universal Equilibrium Validity Criterion

•Trends and simple formulae

•Nomenclature; Proper/Improper

•Guide for diagnostics

•Global Discharge Model

Page 53: Computational Plasma Physics

TU/e

Global Discharge Model Model

Particle Balance Electrons Energy Balance

Energy Balance Heavies

Page 54: Computational Plasma Physics

TU/e

The Electron Particle Balance

Plasma

Wall

A A+ + e+ +e e

A A+ + e

Ion = diff n1SCR(Te) = Da/L2

Thus particle balance Te

Page 55: Computational Plasma Physics

TU/e

The Electron Energy Balance

{H*} .EM {e} ElectroMagnetic {H} Field

{wall

={e} ={H}

eff.

nen1Sheat(kTe - kTh) = /L2 Th Heat branch gives Th

Page 56: Computational Plasma Physics

TU/e

Two Channels: Heating & Creation

= ne n1 Sheat (kTe – kTh) + ne n1 Sion (I+ 3/2 kTe)

elastic heat inelastic creation

= Creation/Total = Creation Efficiency

ne = ()/(Da L-2) Energy Balance gives ne

ne n1 Sheat kTe + ne Da I L -2

Page 57: Computational Plasma Physics

TU/e

dBR single CV compared with PLASIMO

Central T_e and T_h as function of n for Ar cylinder plasma R = 10 mm and power density 106 Wm-3

Page 58: Computational Plasma Physics

TU/e

Valitidy for dBR

But does it works for MIP ?

dBR: Combination of validity criteria diagnostic guides and global models

dBR: Works for ICPs and CCPs

Depends on ...

Page 59: Computational Plasma Physics

TU/e

The Role of Molecules

Ar+

Ar2+

Recall: we must compare Forward and corresponding Backward processes that is: along the same Channel

Page 60: Computational Plasma Physics

TU/e

Grand models; a flavor

Grand models Specific models

MD2D

PLASIMO

Collisional Radiative Me.g. to make Look-up Tablesfor the grand

Examples

“Multi Physics” Mono Physics

Multi

Page 61: Computational Plasma Physics

TU/e

MD2D

n {e}, {A+n}, {An

*} etc.

E {e} solely

No Gas heatingNo flow

Various Particle SourcesReactions

Lean & clean 40 files6000 lines

+ Plasimo In/OutExtravaganza

V

Poisson Potential

Page 62: Computational Plasma Physics

TU/e

MD2D-Applications

PDP plasma TVCFL ignitionDBDNeedleParallel plate reactors (GEC Cell)

Low (average) power plasmas

Page 63: Computational Plasma Physics

TU/e

Plasimo

PhysicoChemistry

MathNumerics

Software Architecture

1034 Files1233 Classes160.000 Lines +

ManualsCVS systemCookingBooks

Page 64: Computational Plasma Physics

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Modeling Platform

3- problem LTE plasma

1- problem SS Heating Rod d/dt Coffee Cooling

2- problem SS Water Flowd/dt

3- problem SS Gas-flow

5- problem non-LTE

Page 65: Computational Plasma Physics

TU/e

PLASIMO is

Not just a model But a Model Platform CFD

For a manifold of plasma conditions

SS and d/dt

Object Oriented C++

Extendable and reusable

Page 66: Computational Plasma Physics

TU/e

General Triptych Structure

Energy CouplingDC

InductiveCapacitivelyMicrowave

Laser

Energy Momentum Particles Configuration Transport Composition

Boundary Conditions

Gas Mixture

ReactionsRelations

Transport Coeffs

Matrix Eqn Solvers

eqns

= -D + u

+ = S

Ray Tracing

Grid generation

Page 67: Computational Plasma Physics

TU/e

PhysicoChemistry

Comes in via Transport Coeffs and Source terms

Collisions providing Rates

Physics: Large Variety Mathematics: Similarities

Base ClassDerived Classes

Page 68: Computational Plasma Physics

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Runtime Configurability

Change : Flowing/non-Flowing Equilibrium Departure type Mixture properties (Chemistry)Discretization methodsAlgorithmMatrix solvers

Functionality abstracted using classes with virtual methods

Self-registering objectsDynamic loading Configuration during runtime

Page 69: Computational Plasma Physics

TU/e

Particle Models; a flavour

Particle behaviorThe EOM

A. No acceleration Ray Tracing

B. AccelerationField moves SwarmsSwarm changes field Monte Carlo collisions

Page 70: Computational Plasma Physics

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Radiative Transfer

Ray-Trace Discretization spectrum. Network of lines (rays) Compute I (W/(m2 .sr.Hz) along the lines

Start outside the plasma with I() = 0. Entering plasma I() grows afterwards absorption.

dI()/ds = j - k()I()

Page 71: Computational Plasma Physics

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Ray Tracing