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Record W3199444388 · doi:10.32393/csme.2021.106

Synthetic Jet Development For Wall Jet Flow Control

2021· article· en· W3199444388 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

VenueProgress in Canadian Mechanical Engineering. Volume 4 · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNew Brunswick Innovation Foundation
KeywordsJet (fluid)Synthetic jetFlow control (data)Computer scienceMechanicsAerospace engineeringPhysicsEngineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

The design and construction of synthetic jet actuators for use in active flow control of a turbulent three-dimensional wall jet was investigated experimentally. Seven actuator designs of varying cavity depth and channel height were evaluated based on hot-wire velocity measurements, maximum RMS velocity outputs, and momentum coefficients. Initially, the synthetic jet actuators were driven with sinusoidal frequency sweeps from 10 Hz to 1510 Hz to identify frequencies associated with the strongest velocity output. For each actuator, momentum coefficients were calculated from sinusoidal inputs at the frequencies that produced the strongest jets. Evaluation of these tests showed that the most successful synthetic jet actuator had a cavity depth of 2 mm and channel height of 1.5 mm; it produced the strongest velocity output with momentum coefficients from 0.03-0.05 at input frequencies of 1100-1150 Hz. Synthetic jet actuators capable of providing these momentum coefficients have been shown from the literature to achieve flow control.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
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
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.189
Teacher spread0.184 · 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