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Record W4323661412 · doi:10.2514/1.j062512

Flow Reattachment on a NACA 0025 Airfoil Using an Array of Microblowers

2023· article· en· W4323661412 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAIAA Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsUniversity of Toronto
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsAirfoilSynthetic jetFlow separationReynolds numberDragFlow control (data)MechanicsWakeAngle of attackWind tunnelChord (peer-to-peer)Vortex generatorNACA airfoilSeparation (statistics)Lift (data mining)Boundary layerActuatorPhysicsMathematicsAerodynamicsVortexEngineeringComputer scienceTurbulenceElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

An array of commercially available synthetic jet actuators was developed for controlling flow separation on a NACA 0025 airfoil. The array is more compact in comparison to standard synthetic jet actuators previously studied for separation control. Wind tunnel experiments were conducted at chord Reynolds number [Formula: see text] and [Formula: see text]. Control of separation was applied by the array through forcing at the wake and shear layer frequencies ([Formula: see text] and [Formula: see text], respectively). Both effectively suppress flow separation, increase lift, and decrease drag. The dynamics of the reattached flow show different feature for the two forcing schemes. The results demonstrate that this array has comparable control effectiveness on separation to other synthetic jet actuators.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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