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Record W3128591958 · doi:10.1088/1741-4326/abe4b2

Comparison between SOLPS-4.3 and the Lengyel Model for ITER baseline neon-seeded plasmas

2021· article· en· W3128591958 on OpenAlex
D. Moulton, P.C. Stangeby, X. Bonnin, R.A. Pitts

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNuclear Fusion · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Toronto
FundersScience and Technology Facilities CouncilEngineering and Physical Sciences Research Council
KeywordsDivertorNeonPlasmaSeedingImpurityScalingAtomic physicsElectron densityFlux (metallurgy)ElectronMechanicsFusion powerMaterials sciencePhysicsComputational physicsTokamakNuclear physicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract If correct, the Lengyel model offers a simple and powerful tool to predict the conditions required for detachment onset in future fusion reactors. We assess its validity against a comprehensive SOLPS-4.3 simulation database of ITER baseline ( Q = 10) neon-seeded plasmas (Pacher et al 2015 J . Nucl . Mater . 463 591). In absolute terms, the Lengyel Model is found to significantly overpredict the simulated impurity concentration required in the ITER outer divertor for outer target ion flux rollover (by a factor ∼4.3 in this particular case). Importantly though, at detachment onset, and even beyond onset, the Lengyel model does give a remarkably accurate prediction of the scaling interdependencies between the electron density at the outer divertor entrance, the parallel energy flux density at the outer divertor entrance, and the impurity concentration in the outer divertor. However, the generalisation of these two key results to other machines, and in the presence of additional physics not included in these simulations, requires further studies. The analysis techniques described here provide a framework for such studies. Regarding the factor ∼4.3 overprediction of the simulated outer divertor impurity concentration, the main contributors to the disagreement are found to be other energy loss mechanisms besides impurity cooling (primarily neutral losses and radial transport) combined with convective energy fluxes near the target, as well as non-constant electron static pressure due to poloidally variable T i / T e . None of these are included in the Lengyel model. By themselves, these do not strongly influence the scaling interdependencies of the main Lengyel parameters over the explored parameter range. The impurity residence time τ is observed to increase with density, which tends to flatten out the impurity concentration scaling at low density, relative to the Lengyel model (which usually assumes constant τ ). In these simulations, however, this flattening out was cancelled by an accumulation of other effects, so that the scaling prediction of the Lengyel model was still well met. A simple physics model is derived for n e τ that matches the simulation data well. Neon is found to migrate from the inner divertor to the outer divertor with increased puffing, thereby increasing the outer divertor neon enrichment. At outer target ion flux rollover, though, the enrichment is approximately independent of the upstream concentration, so that the Lengyel model predicts well the scaling dependency between the upstream impurity concentration and the upstream electron density, both key quantities dictating the operational range of a tokamak.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.000

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 head0.034
GPT teacher head0.300
Teacher spread0.265 · 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