Transcript Detlev Reiter Atomic data and computational models of fusion plasma

Atomic data and computational models of fusion plasma
Detlev Reiter
Forschungszentrum Jülich GmbH, Institut für Energieforschung-4
52425 Jülich, Germany
ADAS workshop 2009, Schloss Ringberg October 4-6, 2009
Forschungszentrum Jülich
in der Helmholtz-Gemeinschaft
Edge/divertor modelling
@ FZ Juelich - KU Leuven
• interdisciplinary
• already a highly integrated field
- plasma physics
- CFD
- rarefied gas dynamics
- opacity
- plasma wall interaction
- atomic physics
- molecular physics
- .....
fusion, technical, astro
fluid-dynamics
aero-dynamics, vacuum
lighting, inertial fusion
Various databases, own
data repository :
ADAS, NIFS, IAEA, …
EIRENE : gas dynamics, radiation, gyro-averaged impurities
ERO
: PWI, microscopic: Erosion and re-deposition
edge code integration: B2-EIRENE (a.k.a. SOLPS….),
EMC3-EIRENE (IPP), EDGE2D-EIRENE (JET)
OSM-EIRENE (ITER.org)
molecular databases (with IAEA, Vienna)
Relative importance of plasma flow forces over chemistry and PWI
I core plasma  II edge region  III divertor
div(nv║)+div(nv┴)= ionization/recombination/charge exchange
II: midplain
III: target
Dominant friction: p + H2
parallel vs.
(turbulent)
cross field
flow
parallel vs.
chemistry
and PWI
driven flow
Well separated: transport – turbulence: good !
core
edgeplasma
plasma
Typical Time Scales in a next step experiment
with B = 10 T, R = 2 m, ne = 1014 cm-3, T = 10 keV
SAWTOOTH CRASH
ELECTRON TRANSIT
ENERGY CONFINEMENT
TURBULENCE
Ωce-1
10-10
ωLH-1
Ωci
10-8
-1
ISLAND GROWTH
τA
10-6
10-4
Atomic &
molecular
processes
Ion drift
waves
Neglect
displacement
Transients
(ELMs)
current,
average
over
gyroangle, (some)
with electrons
Neutral particle
codes, kinetic imp.
transport codes
plasma chemistry
ITM
Gyrokinetics
Codes
10-2
CURRENT DIFFUSION
100
Parallel dynamics:
Ion transit,
Ion collisions
Parallel sound wave
Ditto, electrons
102
104
SEC.
Neglect displacement
current, integrate over
velocity space, average
over surfaces, neglect
ion & electron inertia
Core Transport Codes
2D transport codes
Edge turbulence
turbulent
transport
discharge time-scale
Generic kinetic (transport) equation
(L. Boltzmann, ~1870)
•for particles travelling in a background (plasma)
between collisions
•with (ions) or without (neutrals) forces (Lorentz) acting on
them between collisions
 
Basic dependent quantity: distribution function f ( r , v , t )







f E , 
 v  f E ,   Forces  S E ,   v a E  f E , 
t
Free flight
External source
Absorption

 









  

 

 

  dE   d v s E   E,    f E ,   v s E  E ,    f E, 
0
4
Collisions, boundary conditions
Altogether, just a balance in phase space
Example: MAST (UK)
Plasma temperature in K
Courtesy: S. Lisgo
Characteristics (=Trajectories) of kinetic transport equation
here: MAST, Culham, UK
Here: mainly H, H2, CxHy neutrals
MAST: Geometry and exp. plasma data provided by S. Lisgo, UKAEA, 2007
H2 molecule, status in present More complete models available,
ITER divertor code
still need to be integrated
compiled 1997
E [eV]
H2+
16
35
14
30
n=3
E,F
C
a
B
c
n=2
10
13.6 eV
8
Resonanceb !
6
v=14
4
··
·
2
0
Singlet
Potential Energy (eV)
12
compiled since 2005
25
H2
+
3
+
2
X g
20
+
+
H +H
H*+H
15
5
H2 Triplet system
0
n=4
n=3
1
10
v=3
v=2
v=1
v=0
Courtesy: K. Sawada, D. Wuenderlich
for He, He+: T. Fujimoto, M. Goto
3
a g c u
3
b u
H2
1
X g
0
1
C u
+
1
+
1
B u E,F g
+
H+H
+
2
3
Internuclear Distance (A)
4
Example: MAST (UK), 3D (filament studies)
(Molecular) Gas Density (1 – 3 E20).
Example: MAST (UK), 3D (filament studies)
(Atomic) Gas Density (1 – 3 E19)
EIRENE kinetic transport code (www.eirene.de):
gyro averaged ion kinetic up to edge-core interface
V&V: ongoing:
CxHy source,
CH, C, C++
spectroscopy
MAST: Divertor
TEXTOR: Limiter
Here: CxHy, C, C+, C2+, … atomic & molecular neutrals and ions
MAST: Geometry and exp. plasma data provided by S. Lisgo, UKAEA
Numerical tool for the edge plasma science:
B2-EIRENE code package (ITER.org - FZJ)
Reiter, D., PPCF 33 13 (1991)
Reiter, D., M. Baelmans et al., Fusion Science and Technology 47 (2005) 172.
Kukushkin A. et al., Contr. Plasma Physics (2009), review
Self-consistent description of the magnetized
plasma, and neutral particles produced due to
surface and volume recombination and sputtering
B2: a 2D multi species
(D+, He+,++, C4+..6+,…)
plasma fluid code
At - data:
pre-proc. ??
Computational Grid
Source terms
(Particle,
Momentum,
Energy)
Plasma flow
Parameters
CR codes:
HYDKIN
EIRENE: a Monte-Carlo
neutral particle, trace ion
(He+, C+, C++) and radiation
transport code.
see www.eirene.de
1D core,
0D point reactor
STRAHL, ETS
MACROSCOPIC
B2: a 2D multi species
(D+, He++, C4+..6+,…)
plasma fluid code
Plasma flow
Parameters
CR codes:
(HYDKIN)
EDGE CODES
Source terms
(Particle,
Momentum,
Energy)
EIRENE: a Monte-Carlo
(B2-EIRENE)
neutral particle, trace ion
(He+, C+, C++) and radiation
transport code.
see www.eirene.de
MICROSCOPIC
gyro-kinetic,
N-body
(ERO, PIC)
Hydride Collision Databases
for Technical Plasmas and Fusion Plasmas
Reviewed Database Series 2002-….,
FZ-Jülich (R. Janev, D. Reiter),
www.eirene.de www.hydkin.de
C3Hy
Silane (SiHy)
p,H, H- ,H2 ,H2 ,H3
JUEL 4005, Oct. 2002
Phys. Plasmas,
Vol 11,2, (2004) 780
JUEL 4038, Mar. 2003
Contr. Plas.Phys,
47, 7, (2003) 401-417
JUEL 4105, Dec. 2003
Encycl. Low. Temp.
Pl. 2007 (in russian)
Methane (CHy) C2Hy
JUEL 3966, Feb 2002
Phys. Plasmas,
Vol 9, 9, (2002) 4071
raw data
2004 -- ……(ongoing)
HYDKIN
database
toolbox
Spectral (time scale) analysis
fragmentation pathways
Sensitivity analysis
Interface
EIRENE
3D Monte Carlo
kinetic transport
TEXTOR, JET,
ASDEX, DIII-D,
JT-60, LHD, …..
ITER
NEW
Revisions 04-09:
APID Vol. 16 (2009)
Issue: backward compatibility
NEW: added after Juel-Reports and
PoP papers
NEW: surface reflection database
Choose plasma background
Integration time
Graphical presentation
Printout:
Reflect input as selected
(composition, initial condition,
Influx, transport losses, per species)
Printout:
All individual rates used
Output for interface to EIRENE
Solution, vs. time (distance)
Here: 0  1e-4 s
Species selected for printout and plotting
Same, integration time 0 1e-3
Runtime of online code is independent
of chosen time interval for integration
(same for 1e-6 or 1e+6 s)
Online solution of time-dep. (1D) Hydrocarbon breakup,
for any prescribed divertor plasma conditions, up to C3H8
Spectral analysis:
Identification of reduced models:
ILDM
Very complex reaction chains (approx. 500 individual processes)
in fusion plasmas: catabolic sequence dominant, little: anabolism
Eigenmode analysis of reaction rate equations very simple:
Define “Stiffness parameter”: λmax/ λmin,, ratio of max. to min. eigenvalues
fast slow
Combustion and flame modelling is mathematically analog
to diffusion-reaction modelling of ITER divertor detachment.
Species to be retained
Unfortunately: reduced models („intrinsic low dimensional manifolds, ILDM“)
only applicable at very low plasma temperatures
ILDM
Full reaction
kinetics required
importance of CX-DR over DE-DI channels:
put one CxHy into plasma. How many e,p pairs are neutralized?
CX, DR
DE, DI
p+CxHy  H + CxHy+, CxHy+  DR
Sensitivity analysis:
Z(t)=d(ln[nY])/d(ln<rate>)
Identify, print and plot the most
sensitive parameters:
If <rate> changes by x %
Then nY changes by x * Z %
Breakup of CH4 @ 25 eV
All: DE, I, DI processes
Sensitivity analysis:
Z(t)=d(ln[nY])/d(ln<rate>)
Breakup of CH4 @ 2 eV
All: CX and DR,
DE, I-DI not sensitive
Integrated edge plasma simulation:
“From the barrier to the target”
 computational sciencerectangular
curvilinear
adaptive curvilinear
geometry
Fluid turbulence and ab initio:
GK turbulence simulations
grid free
HPC
physics
3s3v
2s2v
1s2v
Integrated edge transport modeling:
3s
fluid - kinetic – chemistry- PSI
2s
“micro-macro” models
1s
 computational engineering
already now
(connection to topic 5)
Backup Slides
Computational Science Workflow
“Waterfall Model” (1960-th…)
(the dream of code development managers)
1) Requirement (e.g.: integrated fusion code for ITER)
2)
Planning and design
3)
Code (Programming)
4) Test
5) Run
Computational Science and Engineering is moving from “few effects” codes
developed by small teams (1-3 scientists) to “many effect codes” codes
developed by larger teams (10-20 or more).
The reality in large scale code development projects
The process is:
•Very complex
•Risky
•Takes Long
Elastic collisions
Up-to date model for molecular
chemistry
[K. Sawada, T. Fujimoto, 1995]: