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Record W4399271345 · doi:10.2514/6.2024-3345

On the Phase Relation in Aeroacoustic Feedback Loops

2024· article· en· W4399271345 on OpenAlexaff
Romain Gojon, Michaël Bauerheim, Maxime Fiore, Stéphane Moreau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsRelation (database)Phase (matter)AcousticsControl theory (sociology)Computer sciencePhysicsArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Aeroacoustic feedback loops can occur in a variety of flows: high speed jets interacting with a plate or a corner, supersonic non-ideally expanded free jets, grazing flow over a cavity, flow around an airfoil, flow passing two diaphragms in tandem, and flow passing through compressor blade rows, among many others. These feedback loops can induce acoustic tones. The typical model used to predict the corresponding tone frequencies dates back from the 50’s [1], and is still used to this day, with some minor modifications. This model consists of two steps. First, in a shear layer or a boundary layer, an aerodynamic disturbance is convected downstream and amplified through the Kelvin-Helmholtz instability from the starting point to the ending point of the feedback loop. It interacts with a singularity at the ending point, and then generates an acoustic wave propagating upstream. This wave excites the shear layer (or the boundary layer), leading to the formation of a new aerodynamic disturbance, thus generating a new cycle. To apply correctly the original model of Powell consisting of the addition of two propagating times, one needs to know the convection velocity, the speed of sound, the positions of the starting and ending points of the feedback loop, and the phase relations between the hydrodynamic and the acoustic pressure fluctuations on both endings. First, we propose to revisit phase relation in aeroacoustics feedback loop. Then, those phase relations are studied for supersonic impinging jets, and for flow around a airfoil. For the latter case, the phase relation is still an open question in the literature and it is shown that, for the present SD7003 airfoil, a phase shift of 180° is found both at the starting point of the feedback loop, taken here as the separation point, and at the ending point of the feedback loop, that is the trailing edge. This is not in agreement with standard model used in the literature. A 2D toy model is finally derived to mimic the feedback loop arising in airfoil tonal noise. This toy model permits to recover the phase shifts found before for the airfoil tonal noise.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.230
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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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