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Record W4392285809 · doi:10.2514/1.j063327

Plasma Actuator Separation Control Investigated with Spectral Proper Orthogonal Decomposition

2024· article· en· W4392285809 on OpenAlexafffund
Xuan Shi, Pierre E. Sullivan

Bibliographic record

VenueAIAA Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoGovernment of OntarioCompute Canada
KeywordsPlasma actuatorAirfoilDielectric barrier dischargeFlow control (data)MechanicsWakeActuatorSeparation (statistics)Flow (mathematics)Flow separationDynamic mode decompositionMaterials scienceControl theory (sociology)Large eddy simulationPlasmaDetached eddy simulationComputational fluid dynamicsTurbulenceDielectricPhysicsEngineeringComputer scienceElectrical engineeringReynolds-averaged Navier–Stokes equationsOptoelectronics

Abstract

fetched live from OpenAlex

A single dielectric-barrier discharge plasma actuator is an active flow control device that imparts momentum to the fluid through ion acceleration using electromagnetic forces and has been used to suppress flow separation. This paper studies flow over an airfoil and how adding a single dielectric-barrier discharge actuator influences flow characteristics through numerical modeling. Using the spectral proper orthogonal decomposition and large-eddy simulation, flow instabilities are analyzed at their different temporal and spatial scales in the wake region. This study aims to explore the viability of spectral proper orthogonal decomposition for separation control and correlate the decomposed flow modes to the different actuation modes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 science0.0000.000
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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations8
Published2024
Admission routes2
Has abstractyes

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