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Analytical Modeling of Modulated Rotating-Blade Noise : the Skipping Rope and the Darrieus Wind Turbine

2021· article· en· W3164549964 on OpenAlexaff
Michel Roger, Stéphane Moreau

Bibliographic record

VenueJournal of Physics Conference Series · 2021
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversité de Sherbrooke
FundersAgence Nationale de la Recherche
KeywordsRopeSpectrogramAirfoilAerodynamicsStall (fluid mechanics)AcousticsTurbineWind powerNoise (video)Marine engineeringContext (archaeology)EngineeringComputer scienceAerospace engineeringStructural engineeringGeologySpeech recognitionArtificial intelligencePhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract The present study is about the modulations of the aerodynamic broadband noise heard from slowly rotating rotors with few blades. It is aimed at producing a fast-running prediction tool that could be used to assess the nuisance of Vertical-Axis Wind Turbines (VAWT) in the context of urban installation. The simpler case of a skipping rope that only involves part of the modulation effect is addressed as a first step. The rope is split into segments for which an instantaneous sound-radiation model exists to yield an overall spectrogram. Finally, its time signature is reconstructed by additive synthesis. After inspection of existing databases from oscillatory-airfoil experiments, needs for data representative of the dynamic stall of VAWT blades are seen as the missing block to reconstruct a synthetic spectrogram.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Physics Conference SeriesSame topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207