Interaction Between Different
Physical Processes Within
Integrated Predictive
Modeling Simulations
Glenn Bateman
Lehigh University Physics Department
16 Memorial Drive East
Bethlehem, PA 18015
Fusion Simulation Project Workshop
San Diego, CA 17-18 September 2002

Integrated Predictive Tokamak ModelingInteractions between many different kindsof physical processes are computed for:Pedestal
ModelsCore
Transport

Equilibrium
NeutralBeams

ELMs

Integrated
Modeling
Framework

SawtoothOscillations

PelletInjection

Magnetic
Diffusion
Nuclear
Reactions

RF Heating
Current Drive

Impurity
Radiation

NeutralGas

Sources
Sinks
Transport
Equilibrium
shapeLarge-scaleinstabilities
Boundaryconditions

Sawtooth Oscillations « Fast Ion
Heating Profile• Fast ions are spread out across the sawtoothmixing region during each sawtooth crash– Consequently, fast ion heating of the thermal plasmais spread out over the sawtooth mixing region– Fast ions are driven by• Neutral Beam Injection (NBI)• Fusion reactions (e.g., deuterium-tritium reactions produce
fast alpha ions)• Ion Cyclotron Resonance Frequency (ICRF) heating– Stand-alone codes for NBI, alpha heating, or ICRF
generally do not consider this effectNBI Heating Profile inBALDUR Simulation of MASTNBI heating profile is spread out over thesawtooth mixing regionEffect of Sawtooth Crashes on
Heating by Fast Alpha Particles• With each sawtooth crash:– Central temperatures drop as
plasma is spread over thesawtooth mixing region– Fast alpha particles slow
down more rapidlyÞThere is a faster transfer ofpower from fast alphaparticles to thermal plasma– This appears as a transient
spike in Palpha after each crashÞThermal electrons and ionsreheat rapidly• As a result, the fusion burn canrecover from transient low
central temperatures

Boundary Conditions « Confinement• Boundary conditions affect confinement inmany different kinds of tokamak discharges:– H-mode discharges:• A sharply defined pedestal forms at the edge of the plasma• Confinement is enhanced by the pedestal– Especially since core transport models are stiff• Sufficiently good confinement is required to form thepedestal during the L to H-mode transition• Combinations of pedestal and core models are required for
integrated predictive transport simulations– “Supershot” discharges• Wall conditioning was used to minimize recycling in orderto prepare for hot-ion “supershot” discharges in TFTR

Transport « Current Profile• There is the following non-linear feedback loop
in tokamaks:Current profile ® transport ® pressure gradient ®
bootstrap current ® current profile• Usually, the current profile evolves on a slower
time scale than the transport– Magnetic diffusion is slower than thermal transport– Sawtooth oscillations, current drive, and edge
phenomena also affect the current profile• Reversed magnetic shear (ie, low central current)
can produce Internal Transport BarriersThis slide was suggested by Irina VoitsekhovitchTransport « Lower Hybrid Heating• Radio-frequency power absorption depends on
plasma parameters which, in turn, depend on
sources, sinks, boundary, and transport– In a low temperature plasma, there is weak, off-axis
multi-pass heating– As the temperature increases, there is a transition
from weak multi-pass to strong single-pass heating– Single pass heating deposition scales like T-1/2• Lower hybrid can also be used to drive current– Driving current off-axis can produce reversed
magnetic shear, which can produce an Internal
Transport BarrierThis slide was suggested by Irina Voitsekhovitch

Sawtooth Oscillations « Transport« Edge Localized Modes (ELMs)• Heat pulses are produced by sawtoothoscillations and (cold pulses) by ELMs
– Sawtooth crashes and ELMs are periodic abrupt
redistributions of the plasma profiles– Heat pulses are observed to propagate much fasterthan the background heat transport– Ion particle and ion momentum pulses also
propagate through the plasma– Stiff, non-linear transport models are used to model
the observed pulse propagation• This is one way to discriminate between different models– Large sawteeth and ELMs can degrade confinement

Impurity Influx ®
Enhanced Confinement• It is observed on DIII-D and other tokamaks thata sudden impurity influx produces enhanced
confinement– Strong flow shear is produced by the impurity influx• Integrated modeling simulations using theNational Transport Code Collaboration– Showed that flow shear reduced the transport toneoclassical values– Were able to predict the experimentally observed
temperature profiles

INCREASE IN ExB SHEARING RATE IS A NECESSARY CONDITION
FOR CONFINEMENT IMPROVEMENT• Body Text– Second Level• Third Level– Fourth Level» Fifth Level

Simulations are used to test:
lEffects of ExB shearing fromexperimental wExB to 0l
Effects of changing Zeff (3.2 ®
1.4) and ne(r) after theimproved state is establishedÞ Neon injection may be used as atrigger

11 MURAKAMI: IAEA00

Density Limit in Tokamaks• Several effects are believed to play a role indetermining the density limit in tokamaks:– Gas puffing at high density produces a steep density
gradient near the edge of the plasma– The steep density gradient enhances transport near
the edge of the plasma– Impurities radiate most of the power at high density• This produces a “radiative collapse” of the plasma– As the edge of the plasma cools, the plasma current
cannel shrinks– As the current channel shrinks, the current gradientdrives MHD instabilities that lead to disruption

Integrated Modeling Issues - 1• Which models are correct?
– There are several different models for• Core transport• H-mode pedestal• Large scale instabilities (such as sawtooth oscillations)– Simulations using these different models match
experimental data about equally well
• RMS deviations are in the 10% to 20% range– The different models predict different performance
when extrapolated to fusion reactor designs• For example, the IFS/PPPL model predicted poor
performance for ITER-EDA while the Multi-Mode model
predicted ignition– We need the predictions to converge together

Integrated Modeling Issues - 2• Specialized computer codes have gotten way
ahead of integrated modeling codes– Specialized codes to compute plasma turbulence
and large-scale instabilities are way ahead of themodels used within integrated modeling codes– Scrape-off-layer codes (such as UEDGE) have notyet been combined with most core modeling codes• Some issues are neglected– For example, predicting the impurity concentration
in tokamak plasmas• The performance of fusion reactors is predicted to besensitive to high levels of impurity concentration

Integrated Modeling Issues - 3• What constitutes an adequate test of integrated
predictive modeling simulations?
– How good does the comparison with experimentaldata have to be, before we have confidence in themodels and simulations?
– How much difference does there have to be,
before we can reject a model?
– How sophisticated do the models have to be,
before they are accepted by theoreticians?
– When are the models and codes good enough totrust the results of fusion reactor simulations?