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Record W6931983689 · doi:10.5281/zenodo.7740607

Power Dissipation of an Inductively Coupled Plasma Torch under E Mode Dominated Regime

2021· article· en· W6931983689 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldComputer Science
TopicFace and Expression Recognition
Canadian institutionsnot available
Fundersnot available
KeywordsTorchPlasma torchDissipationElectromagnetic coilInductively coupled plasmaNozzlePlasmaCoolant

Abstract

fetched live from OpenAlex

This paper focuses on the power dissipation of a plasma torch used for an optical surface fabrication process. The process utilizes an inductively coupled plasma (ICP) torch that is equipped with a De-Laval nozzle for the delivery of a highly collimated plasma jet. The plasma torch makes use of a self-igniting coil and an intermediate co-axial tube made of alumina. The torch has a distinctive thermal and electrical response compared to regular ICP torches. In this study, the results of the power dissipation investigation reveal the true efficiency of the torch and discern its electrical response. By systematically measuring the coolant parameters (temperature change and flow rate), the power dissipation is extrapolated. The radio frequency power supply is set to 800 W, E mode, throughout the research presented in this study. The analytical results of power dissipation, derived from the experiments, show that 15.4% and 33.3% are dissipated by the nozzle and coil coolant channels, respectively. The experiments also enable the determination of the thermal time constant of the plasma torch for the entire range of RF power.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.263
Teacher spread0.233 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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