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Record W2522849491 · doi:10.1109/tps.2016.2606484

High-Voltage, High-Frequency Pulse Generator for Nonequilibrium Plasma Generation and Combustion Enhancement

2016· article· en· W2522849491 on OpenAlexafffund
M. D. G. Evans, Jeffrey M. Bergthorson, Sylvain Coulombe

Bibliographic record

VenueIEEE Transactions on Plasma Science · 2016
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaSiemensMcGill University
KeywordsMaterials sciencePlasmaPulse generatorMarx generatorVoltageGenerator (circuit theory)Pulse repetition frequencyCapacitive sensingPulsed powerPulse durationRise timeElectrical engineeringAtomic physicsPhysicsPower (physics)OpticsLaserEngineering

Abstract

fetched live from OpenAlex

This paper outlines the design and implementation of a solid-state high-voltage, high-frequency pulse generator used to drive capacitive loads and particularly, nonequilibrium plasmas at atmospheric pressure. The generator is capable of producing open circuit pulses of 0-12 kV with a 300 ns duration (full-width at half-maximum) at a repetition frequency of 0-25 kHz. The working principles of the generator are presented, along with its electrical diagnostics to illustrate its operation with capacitive loads. The generator was applied to a pin-to-plane electrode configuration to generate a diffuse nonequilibrium plasma discharge with peak voltage of 12 kV. Energy deposition and average power required to drive the discharges in open air at 25 kHz were calculated to be 112 μJ/pulse and 2.80 W. The generator was also applied to lean, stagnation-plate stabilized V-shaped flames to increase their blowoff velocity. A 28%-51% increase of the blowoff velocity is observed using a discharge with the peak voltage of 6.2 kV, and the repetition rate of 25 kHz.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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