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Record W2142206837 · doi:10.3390/su4061104

Noise Pollution Prevention in Wind Turbines: Status and Recent Advances

2012· article· en· W2142206837 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.

Bibliographic record

VenueSustainability · 2012
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsWind powerNoise pollutionNoise (video)Noise controlTurbineEnvironmental scienceAerodynamicsMarine engineeringTrailing edgeEngineeringNoise reductionComputer scienceAerospace engineeringElectrical engineeringStructural engineering

Abstract

fetched live from OpenAlex

The global push towards sustainability has led to increased interest in alternative power sources other than coal and fossil fuels. One of these sustainable sources is to harness energy from the wind through wind turbines. However, a significant hindrance preventing the widespread use of wind turbines is the noise they produce. This study reviews recent advances in the area of noise pollution from wind turbines. To date, there have been many different noise control studies. While there are many different sources of noise, the main one is aerodynamic noise. The largest contributor to aerodynamic noise comes from the trailing edge of wind turbine blades. The aim of this paper is to critically analyse and compare the different methods currently being implemented and investigated to reduce noise production from wind turbines, with a focus on the noise generated from the 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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.402

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 head0.005
GPT teacher head0.247
Teacher spread0.242 · 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