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Record W4376863500 · doi:10.1080/10420150.2023.2186876

Design and implementation of a versatile H-bridge power supply for experiments on the STOR-M Tokamak

2023· article· en· W4376863500 on OpenAlexafffund
Heba Bsharat, Michael Patterson, C. Xiao

Bibliographic record

VenueRadiation effects and defects in solids · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTokamakWaveformElectrical engineeringInsulated-gate bipolar transistorCurrent (fluid)Bipolar junction transistorCapacitorPower (physics)PhysicsVoltageTransistorEngineeringPlasma

Abstract

fetched live from OpenAlex

An H-bridge power supply has been developed for different experiments on the STOR-M tokamak. Four insulated-gate bipolar transistors (IGBTs) are used to guide the current to the load from a capacitor bank discharge. The timing signal to the gates of the IGBTs is controlled by a field programmable gate array (FPGA). The power supply can be programmed to drive either a sinusoidal current waveform to an inductive load or a bipolar rectangular current waveform to a resistive load. The maximum frequency and current tested for the sinusoidal current waveform are 25 kHz and 2200 A, respectively. For bipolar current waveforms, the maximum current tested is 1500 A at 3 kHz. The sinusoidal current to a set of helical coils was used for the Resonant Magnetic Perturbation (RMP) experiments and the bipolar rectangular current waveform was used for both the electrode biasing experiments and the RMP experiments on the STOR-M 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.018
GPT teacher head0.322
Teacher spread0.304 · 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 designBench or experimental
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

Citations1
Published2023
Admission routes2
Has abstractyes

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