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Record W2053042062 · doi:10.1063/1.3100180

Porous plug gas injection systems for studies of hydrocarbon dissociation and transport in the DIII-D tokamak

2009· article· en· W2053042062 on OpenAlexaff
A.G. McLean, J.W. Davis, P.C. Stangeby, N.H. Brooks, R. M. Ellis, A.A. Haasz, D.L. Rudakov, W. P. West, D.G. Whyte, C.P.C. Wong

Bibliographic record

VenueReview of Scientific Instruments · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDivertorDIII-DMaterials scienceMethaneTokamakHydrocarbonPorositySpark plugPlasmaInjectorAnalytical Chemistry (journal)Nuclear engineeringChemistryComposite materialChromatographyNuclear physicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

A probe has been designed, constructed, and successfully used to inject methane into the DIII-D lower divertor in a manner imitating natural release by chemical erosion. This porous plug injector (PPI) probe consists of a self-contained gas reservoir with an integrated pressure gauge and a 3 cm diameter porous surface through which gas is injected into the lower divertor of the tokamak. The probe is positioned flush with the divertor target surface by means of the divertor materials evaluation system. Two gas delivery systems were developed: in the first, gas flow is regulated by a remotely controlled microvalve and in the second by a fixed micro-orifice flow restrictor. Because of the large area of the porous surface through which gas is admitted, the injected hydrocarbon molecules see a local carbon surface (>90% carbon) similar to that seen by hydrocarbons being emitted by chemical sputtering from surrounding carbon tiles. The distributed gas source also reduces the disturbance to the local plasma while providing sufficient signal for spectroscopic detection. In situ spectroscopic measurements with the PPI in DIII-D allow the direct calibration of response for measured plasma conditions from a known influx of gas.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.307
Teacher spread0.283 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations5
Published2009
Admission routes1
Has abstractyes

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