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Record W2141780985

Vertical compact torus injection into the STOR-M Tokamak

2006· article· en· W2141780985 on OpenAlexfundno aff
Dazhi Liu

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2006
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTokamakThermonuclear fusionToroidPlasmaMagnetic fieldPhysicsTore SupraAtomic physicsFusion powerMaterials scienceNuclear magnetic resonanceMechanicsNuclear physics
DOInot available

Abstract

fetched live from OpenAlex

Central fuelling is a fundamental issue in the next generation tokamak-ITER (International Thermonuclear Experimental Reactor).It is essential for optimization of the bootstrap current which is proportional to the pressure gradient of trapped particles.The conventional fusion reactor fuelling techniques, such as gas puffing and cryogenic pellet injection, are considered inadequate to fulfill this goal due to premature ionization caused by high plasma temperature and density.Compact Torus (CT) injection is a promising fuelling technique for central fuelling a reactor-grade tokamak.An accelerated CT is expected to penetrate into the core region and deposit fuel there provided the CT kinetic energy density exceeds the magnetic energy density in a target plasma.This process is complicated and involves CT penetration into an external magnetic field, a CT stopping mechanism, magnetic reconnection, and excitation of plasma waves.CTs can be injected at different angles with respect to the tokamak toroidal magnetic field, either horizontally or vertically.Normally, CTs are injected radially His untiring willingness to teach and encourage me made the whole course of this thesis work highly enjoyable.His dedication to high quality experimental plasma physics research has been a great inspiration.I am especially fortunate to have witnessed Prof. Xiao's talent for identifying important research problems and solving technical problems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.146
Teacher spread0.142 · 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.

Study designQualitative
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

Citations2
Published2006
Admission routes1
Has abstractyes

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