MétaCan
Menu
Back to cohort
Record W2070809201 · doi:10.1115/1.4005751

Aerodynamic Performance of a Small Horizontal Axis Wind Turbine

2012· article· en· W2070809201 on OpenAlexafffundabout
Maryam Refan, Horia Hangan

Bibliographic record

VenueJournal of Solar Energy Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsWestern University
FundersNational Renewable Energy LaboratoryNatural Sciences and Engineering Research Council of Canada
KeywordsAerodynamicsTurbineRotor (electric)Wind powerHorizontal axisWind speedSmall wind turbineRange (aeronautics)Wind tunnelMarine engineeringTip-speed ratioMomentum (technical analysis)Planetary boundary layerTurbine bladeComputer scienceBoundary layerMechanicsStructural engineeringPhysicsAerospace engineeringMeteorologyEngineeringMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The aerodynamic performance of an upwind, three-bladed, small horizontal axis wind turbine (HAWT) rotor of 2.2 m in diameter was investigated experimentally and theoretically in order to assess the applicability of the blade element momentum (BEM) theory for modeling the rotor performance for the case of small HAWTs. The wind turbine has been tested in the low and high speed sections of the Boundary Layer Wind Tunnel 2 (BLWT2) at the University of Western Ontario (UWO) in order to determine the power curve over a wide range of wind speeds. Afterward, the BEM theory has been implemented to evaluate the rotor performance and to investigate three-dimensionality effects on power prediction by the theory. Comparison between the theoretical and experimental results shows that the overall prediction of the theory is within an acceptable range of accuracy. However, the BEM theory prediction for the case of small wind turbines is not as accurate as the prediction for larger wind turbines.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.006
GPT teacher head0.172
Teacher spread0.166 · 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 designBench or experimental
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

Citations61
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Solar Energy EngineeringSame topicWind Energy Research and DevelopmentFrench-language works237,207