Forschungszentrum J

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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
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Edge/divertor modelling _at_ 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-dynam
ics, 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)
 
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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
div(nv)div(nv-) ionization/recombination/charge
exchange
II midplain
parallel vs. (turbulent) cross field flow
parallel vs. chemistry and PWI driven flow
III target
Dominant friction p H2
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core plasma
edge plasma
Well separated transport turbulence good !
Typical Time Scales in a next step experiment
with B 10 T, R 2 m, ne 1014 cm-3, T 10
keV
SEC.
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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
Free flight
External source
Absorption
Collisions, boundary conditions
Altogether, just a balance in phase space
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Example MAST (UK)
Plasma temperature in K
Courtesy S. Lisgo
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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
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H2 molecule, status in present ITER divertor code
compiled 1997
Courtesy K. Sawada, D. Wuenderlich
for He, He T. Fujimoto, M. Goto
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Example MAST (UK), 3D (filament studies)
(Molecular) Gas Density (1 3 E20).
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Example MAST (UK), 3D (filament studies)
(Atomic) Gas Density (1 3 E19)
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EIRENE kinetic transport code (www.eirene.de)
gyro averaged ion kinetic up to edge-core
interface
VV 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
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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
Plasma flow Parameters
B2 a 2D multi species (D, He,, C4..6,)
plasma fluid code
CR codes HYDKIN
At - data pre-proc. ??
Source terms (Particle, Momentum, Energy)
EIRENE a Monte-Carlo neutral particle, trace ion
(He, C, C) and radiation transport code.
Computational Grid
see www.eirene.de
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1D core, 0D point reactor STRAHL, ETS
MACROSCOPIC
EDGE CODES (B2-EIRENE)
processed data (integrated, condensed, bundled,)
Data as unprocessed as possible
MICROSCOPIC
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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
Methane (CHy)
C2Hy
C3Hy
Silane (SiHy)
JUEL 3966, Feb 2002 Phys. Plasmas, Vol 9, 9,
(2002) 4071
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)
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raw data
2004 -- (ongoing)
Spectral (time scale) analysis
HYDKIN database toolbox
fragmentation pathways
Sensitivity analysis
Interface
EIRENE 3D Monte Carlo kinetic transport
TEXTOR, JET, ASDEX, DIII-D, JT-60, LHD, ..
ITER
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NEW
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Revisions 04-09 APID Vol. 16 (2009)
Issue backward compatibility
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NEW added after Juel-Reports and PoP
papers
NEW surface reflection database
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Choose plasma background Integration
time Graphical presentation
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Printout Reflect input as selected (composition
, initial condition, Influx, transport losses,
per species)
Printout All individual rates used Output for
interface to EIRENE
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Solution, vs. time (distance) Here 0 ? 1e-4 s
Species selected for printout and plotting
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Same, integration time 0? 1e-3
Runtime of online code is independent of chosen
time interval for integration (same for 1e-6 or
1e6 s)
Online solution of time-dep. (1D) Hydrocarbon
breakup, for any prescribed divertor plasma
conditions, up to C3H8
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Spectral analysis Identification of reduced
models ILDM
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• 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 ?max/ ?min,, ratio
  of max. to min. eigenvalues

fast
slow
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Combustion and flame modelling is mathematically
analog to diffusion-reaction modelling of ITER
divertor detachment. Unfortunately reduced
models (intrinsic low dimensional manifolds,
ILDM) only applicable at very low plasma
temperatures
Full reaction kinetics required
ILDM
Species to be retained
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importance of CX-DR over DE-DI channels put one
CxHy into plasma. How many e,p pairs are
neutralized?
DE, DI
CX, DR
pCxHy ? H CxHy, CxHy ? DR
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Sensitivity analysis Z(t)d(lnnY)/d(lnltrategt)
Identify, print and plot the most sensitive
parameters If ltrategt changes by x Then nY
changes by x Z
Breakup of CH4 _at_ 25 eV
All DE, I, DI processes
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Sensitivity analysis Z(t)d(lnnY)/d(lnltrategt)
Breakup of CH4 _at_ 2 eV
All CX and DR, DE, I-DI not sensitive
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Integrated edge plasma simulation From the
barrier to the target
Fluid turbulence and ab initio GK turbulence
simulations ? computational science

• Integrated edge transport modeling
• fluid - kinetic chemistry- PSI
• micro-macro models
• computational engineering
• already now

(connection to topic 5)
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Backup Slides
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Computational Science Workflow Waterfall Model
(1960-th)(the dream of code development
managers)

• 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).

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The reality in large scale code development
projects

• The process is
• Very complex
• Risky
• Takes Long

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Elastic collisions
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Up-to date model for molecular chemistry
K. Sawada, T. Fujimoto, 1995