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Record W2942611582 · doi:10.1121/1.5098776

Wind turbine audibility calculations inside dwellings

2019· article· en· W2942611582 on OpenAlexaff
Stephen E. Keith, David S. Michaud, Katya Feder, Victor Soukhovtsev, Sonia A. Voicescu, Allison R. Denning, Jason Tsang, Norm Broner, Werner Richarz

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2019
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsTransport CanadaUniversity of VictoriaNova Scotia Health AuthorityHealth Canada
Fundersnot available
KeywordsTurbineAcousticsEnvironmental scienceNoise (video)BroadbandLoudspeakerSound pressureComputer sciencePhysicsTelecommunicationsEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

The objective of the current paper was to characterize indoor wind turbine sound pressure levels (SPLs) to assess the audibility of wind turbine noise indoors, accounting for window opening, frequency spectra, and presbycusis. Loudspeaker generated noise was used to determine the outdoor to indoor SPL differences at 11 representative dwellings using ISO 140-5:1998. The procedure was extended to 16 Hz. With windows closed, indoor broadband A- and C-weighted SPLs were lower by 25.9 and 15.3 dB, respectively, for wind turbine noise spectra. With windows opened, the corresponding results were 13.8 and 9.9 dB, respectively. Standard deviations for these results were 3 dB so that indoor and outdoor SPL would tend to be highly correlated. For 35 dBA outdoor SPL, the indoor SPL was potentially audible at frequencies as low as 31.5 Hz. Specifically, at 35 dBA, 80% to 100% of adults below the age of 60 years, would potentially be able to hear wind turbine noise indoors with windows partially open. This would drop to 10% to 30% with closed windows. Uncertainties around these estimates are discussed.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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 designNot applicable
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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

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