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Record W2318241481 · doi:10.2514/1.j055104

Aeroacoustic Simulations of a Simplified High-Lift Device Accounting for Some Installation Effects

2016· article· en· W2318241481 on OpenAlexafffund
Pablo Salas, Stéphane Moreau

Bibliographic record

VenueAIAA Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversité de Sherbrooke
FundersMitacsCompute Canada
KeywordsAnechoic chamberAeroacousticsAcousticsDirectivitySound powerWind tunnelMach numberJet (fluid)MechanicsLift (data mining)Large eddy simulationDetached eddy simulationSound pressureComputational fluid dynamicsPhysicsEngineeringTurbulenceReynolds-averaged Navier–Stokes equationsComputer science

Abstract

fetched live from OpenAlex

The aeroacoustic noise of a simplified wing-flap configuration placed in an open-jet anechoic wind tunnel is investigated by compressible wall-resolved large-eddy simulations possibly coupled with the Ffowcs-Williams and Hawkings acoustic analogy. The numerical domain includes the nozzle and the anechoic chamber, which allows the direct taking of the installation effects into account. The simulated span (25% of the flap chord) is the largest one simulated so far for this configuration and, more generally, at this high Reynolds number. The results of the simulation are validated with the extensive experimental database for the chosen configuration. A good overall agreement with experimental data is achieved for all mean and fluctuating velocities, as well as wall pressures on the wing and the flap, especially the power spectral densities, the convection velocities, and even the streamwise and spanwise coherences on both elements. Similar good predictions of the far-field acoustic pressure using a hybrid approach are achieved, although the acoustic analogy does not allow taking into account the jet noise given that the Ffowcs-Williams and Hawkings surfaces are placed within the jet core. The acoustic results obtained with the acoustic analogy are also compared with the numerical microphones placed in the far field, showing a good agreement up to the mesh cut-ff frequency. The dilatation field and the sound directivity stress that the flap and wing trailing edges are the dominant noise sources of the wing-flap configuration, with significant diffraction effects on the flap side. Evidence of slight boundary-layer instabilities is also shown close to the flap trailing edge.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.229
Teacher spread0.221 · 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

Citations27
Published2016
Admission routes2
Has abstractyes

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