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Record W4389541026 · doi:10.17118/11143/20986

Study of the wake flow downstream of two oscillating vanes

2023· article· en· W4389541026 on OpenAlexaffabout
Xiaoyang Zhang, Dominique Poirel, A. Benaïssa, Weixing Yuan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsNational Research Council CanadaRoyal Military College of Canada
Fundersnot available
KeywordsWakeDownstream (manufacturing)Flow (mathematics)MechanicsAerospace engineeringPhysicsEnvironmental scienceMarine engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract: Towards modelling aerodynamic and aeroelastic response to gusts, a capability of generating controllable perturbed flow was developed for a low-speed wind tunnel of the Royal Military College of Canada (RMC). The experimental setup consisted of two NACA0015 vanes in the freestream. Two independent servo motors were used to actuate the oscillating vanes thus turning the incoming flow, and generating transverse and/or horizontal flow perturbation. A wake flow survey was carried out for the test section downstream of the vanes using an X-hot-wire probe. Both static and dynamic scenarios were investigated. The study of the static configuration was conducted to help the understanding of the dynamic configuration. For the static scenario, the distribution of both the averaged velocity and turbulence intensity of the airflow were obtained along the vertical and streamwise directions. The spectrum of experimental data confirmed intense von Ka´rma´n vortex shedding in the wake area. For the dynamic scenario, oscillating frequencies of vane motion and their super-harmonics were dominant in the spectral plots. The streamwise location range, where the generated vertical flow variation had a nearly uniform amplitude, was determined. It will be utilized as the future location to mount the test wing. The current flow survey and scheduled study of gust effects on the static test wing are building a foundation for our planned aeroelastic investigations.

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 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 score0.012
Threshold uncertainty score0.117

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 teacher head, 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

Citations1
Published2023
Admission routes2
Has abstractyes

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