TRANSP Tests Of TGLF and Predictions For ITER Page: 3 of 8
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TRANSP tests of TGLF and predictions for ITER
R.V. Budny', Xingqiu Yuan1, S. Jardine, G. Hammett', B.A. Grierson',
G.M. Staebler2, J.E. Kinsey2, and JET EFDA Contributors*
1PPPL, P.O. Box 451, Princeton, NJ 08543, USA; 2General Atomics, San Diego, CA, USA
Princeton Plasma Physics Laboratory, Princeton, NJ 08543, USA
1. Introduction. Gyro kinetic simulations of turbulence capture some of the features observed in
transport, fluctuations, and correlations measured in tokamak plasmas. These codes calculations are
CPU intensive, and are not practical for incorporation in present time-dependant transport codes, so
reduced models based on these gyro kinetic codes are being used. An example is the TGLF model [1]
which is a quasilinear gyrofluid model calibrated to nonlinear results from the GYRO code [2]. Recently
TGLF has been incorporated into TRANSP [3].
Analysis of experimental data using TRANSP with such models provides fundamental understanding of
turbulent transport. Predictions of ITER performance with various plasma scenarios using such models
are useful for optimizing design and for exposing issues that can be addressed in present experiments and
theory. For instance, which combinations of heating, torquing, and current drive are optimal. Another
application is for nuclear licensing (e.g. system integrity, neutron rates). Others are generating inputs
for design of diagnostic systems and for theoretical studies. An example of the later is Alfv6n Eigenmode
and AE-induced loss of fast ions. The beam ion distribution can either enhance or reduce the alpha
pressure drive of the AE instability. The AE instability can cause dangerous amounts of fast ion losses,
as was seen in TFTR.
The TRANSP code is being used for self-consistent predictive modeling for ITER [4-6]. The time evolu-
tion of profiles of temperatures and toroidal rotation w9 have been predicted assuming boundary values
using the GLF23 model [7]. Time-dependent simulations are needed to study efficient startup, safe shut-
down, and transients such as magnetic diffusion, sawteeth, and ash accumulation.
A new solver PT-SOLVER has been added to TRANSP for stiff transport models. It incorporates TGLF,
which includes more physics than does GLF23, but which is much more challenging numerically. Bench-
marking and testing of this solver have been reported [3]. Recently this solver is being used to predict
densities, temperatures, and angular momentum. For predicting ITER prior to experimental results all of
the fields need to be predicted. Here new results verifying, validating, and predicting using PT-SOLVER
are presented.
2. PT-SOLVER. The new solver is modular, parallel, and multi-regional. PT-SOLVER integrates
the highly nonlinear time-dependent equations for ion and electron temperatures, densities, and toroidal
angular momentum with implicit Newton iteration methods. The user controls the choice of transport
models attached to the solver, with a range of neoclassical and/or turbulent, or semi-empirical or data
driven choices available. Besides TGLF, GLF23, and MMM [8], the neoclassical models NEO [9]and
Chang-Hinton are included.
Two options are available in TGLF for accounting for the turbulence mitigation form E x B flow shearing.
One is the "quench rule" which compares the local magnitudes of the maximum growth and E x B flow
shearing rates. The other is a new "spectral shift" rule [10]. E x B flow shearing rate induced by the NB
torques is calculated by TRANSP using the self-consistent pressure and magnetic fields. Comparable
predictions result from either.
3. Verification. To asses if TGLF is correctly installed in PT-SOLVER, it is being verified by compar-
ing with the TGLF implementations in the XPTOR and TGYRO codes. Since the numerical schemes
are different in these codes, XPTOR and TGYRO modes have been built in PT-SOLVER for compar-
isons. The PT-SOLVER standalone runs are performed on 64 processors and take about 10-40 hours
for numerically accurate solutions. The three codes give predictions for temperatures in approximate
agreement.
4. Validation. To asses if TGLF in PT-SOLVER is a plausible candidate for ITER predictions, it
is being tested by comparing with experimental results. Several issues make comparisons challenging.
Accurate measurements are needed, including profiles of ne, impurity and fast ion densities, T1, vto,
Zeff, Prad, and PCx-loss. These are important for deducing profiles of the energy, angular momentum,
and species flows. Plasma conditions with minimal effects on transport from MHD and anomalous fast
ion losses are needed since these effects are not included in the transport modeling. PT-SOLVER with
TGLF can predict ne using measured Zeff but the particle source rates are needed. Uncertainties in the
particle source rates affect the simulations. Core fueling profiles from NB are calculated by NUBEAM in
TRANSP. Wall fueling profiles from gas puffing and recycling are calculated by FRANTIC in TRANSP.
The in-flows through the boundary can be estimated from Ha data [11]. Since there are large uncertain-
ties in the in-flows, here they are scaled in PT-SOLVER to produce the measured average densities.
Another uncertainty is transport near the magnetic axis. Many plasmas of interest for ITER have saw-
teeth. An interchange instability criterion is computed in TGLF and the model is not valid for radii
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Robert V Budny, et al. TRANSP Tests Of TGLF and Predictions For ITER, article, June 2, 2013; Princeton, New Jersey. (https://digital.library.unt.edu/ark:/67531/metadc871522/m1/3/: accessed March 19, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.