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Record W3118752766 · doi:10.2514/6.2021-1491

Study of Surface Dielectric Barrier Discharge Plasma Actuator in Post-Combustion Environments

2021· article· en· W3118752766 on OpenAlex
Mitch Collett, Jason Etele

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA Scitech 2021 Forum · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsPlasmaPlasma actuatorPlasma cleaningMaterials scienceIonIonizationHydrogenAtomic physicsDielectric barrier dischargeDielectricSputteringChemistryOptoelectronicsNanotechnologyThin film

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-1491.vid This paper compares the generation and propagation of plasma generated by a surface dielectric barrier discharge (SDBD) plasma actuator in gases commonly found in a post-combustion environment. Simulations are performed at standard atmospheric temperature and pressure conditions for a plasma generated by a 1.2 kV SDBD over 50 ns. Results contrast the behavior of plasma generated in molecular nitrogen with that of carbon dioxide, carbon monoxide, hydrogen and water vapor. Salient features of the plasma generated in different gases are found to be dependent on the ionization and transport properties of the gases. Ion densities are found to be on the order of 10^21 m^-3 in N2, H2O, H2 and CO2, and on the order of 10^19 m^-3 in CO. Changes in ion mobility between 66%-485% result in changes in the plasma propagation by 84%-230% when compared to N2 plasma. It is also shown that the ion mobility of H2+, 485% that of N2+ ion mobility, is sufficient enough to maintain a streamwise electric potential gradient in the region behind the plasma head.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.857

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 studies0.0000.000
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 head0.005
GPT teacher head0.193
Teacher spread0.189 · 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