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Record W2606468089 · doi:10.1016/j.nme.2017.03.039

OEDGE modeling for the planned tungsten ring experiment on DIII-D

2017· article· en· W2606468089 on OpenAlexaff
J.D. Elder, P.C. Stangeby, T. Abrams, Rui Ding, A.W. Leonard, A.G. McLean, D.L. Rudakov, E.A. Unterberg, J.G. Watkins

Bibliographic record

VenueNuclear Materials and Energy · 2017
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Toronto
FundersU.S. Department of Energy
KeywordsDivertorTungstenDIII-DPlasmaTokamakSputteringAtomic physicsMaterials scienceImpurityNuclear physicsChemistryPhysicsNanotechnologyMetallurgyThin film

Abstract

fetched live from OpenAlex

The OEDGE code is used to model tungsten erosion and transport for experiments with toroidal rings of high-Z metal tiles in the DIII-D tokamak. Such modeling is needed for both experimental and diagnostic design to have estimates of the expected core and edge tungsten density and to understand the various factors contributing to the uncertainties in these calculations. OEDGE simulations are performed using the planned experimental magnetic geometries and plasma conditions typical of both L-mode and inter-ELM H-mode discharges in DIII-D. OEDGE plasma reconstruction based on specific representative discharges for similar geometries is used to determine the plasma conditions applied to tungsten plasma impurity simulations. A new model for tungsten erosion in OEDGE was developed which imports charge-state resolved carbon impurity fluxes and impact energies from a separate OEDGE run which models the carbon production, transport and deposition for the same plasma conditions as the tungsten simulations. These values are then used to calculate the gross tungsten physical sputtering due to carbon plasma impurities which is then added to any sputtering by deuterium ions; tungsten self-sputtering is also included. The code results are found to be dependent on the following factors: divertor geometry and closure, the choice of cross-field anomalous transport coefficients, divertor plasma conditions (affecting both tungsten source strength and transport), the choice of tungsten atomic physics data used in the model (in particular ionization rate for W-atoms), and the model of the carbon flux and energy used for calculating the tungsten source due to sputtering. Core tungsten density is found to be of order 1015 m−3 (excluding effects of any core transport barrier and with significant variability depending on the other factors mentioned) with density decaying into the scrape off layer. For the typical core density in the plasma conditions examined of 2 to 4 × 1019 m−3, this represents a concentration on the order of 5 × 10−5.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.257
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2017
Admission routes1
Has abstractyes

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