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Record W3035611842 · doi:10.1063/1.5131439

A model for plasma–neutral fluid interaction and its application to a study of CT formation in a magnetized Marshall gun

2020· article· en· W3035611842 on OpenAlexafffund
Carl Dunlea, C. Xiao, Akira Hirose

Bibliographic record

VenuePhysics of Plasmas · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsGeneral Fusion (Canada)University of Saskatchewan
FundersGeneral FusionNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Saskatchewan
KeywordsPhysicsPlasmaAtomic physicsElectronBiasingIonizationRadiative coolingRadiative transferTorusTokamakElectron densityIonNuclear physicsVoltageOpticsAstrophysics

Abstract

fetched live from OpenAlex

A model for plasma/neutral fluid interaction was developed and included in the implementation of non-linear MHD equations to a new code framework. The source rates of ion, electron, and neutral fluid momentum and energy due to ionization and recombination are derived using a simple method that enables the determination of the volumetric rate of thermal energy transfer from electrons to photons and neutral particles in the radiative recombination reaction. This quantity cannot be evaluated with the standard formal procedure of taking moments of the relevant collision operator and has been neglected in other studies. The plasma/neutral fluid interaction model was applied to study compact torus (CT) formation in the Super-Magnetized Ring Test (SMRT) and Spherical Compact Toroid (SPECTOR) magnetized Marshall guns, enabling clarification of the mechanisms behind the significant increases in CT electron density that are routinely observed well after formation on the SPECTOR experiment. Neutral gas, which remains concentrated below the gas valves after CT formation, diffuses up the gun barrel to the CT containment region where it is ionized, leading to the observed electron density increases. This understanding helps account for the exceptionally significant increase in temperature and the markedly reduced density, observed during the electrode edge biasing experiment conducted on SPECTOR. It is thought that edge fueling impediment, a consequence of a biasing-induced transport barrier, is largely responsible for the observed temperature increase and density decrease.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.410

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)0.0000.000

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 head0.041
GPT teacher head0.299
Teacher spread0.258 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

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