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Record W2027596546 · doi:10.2514/6.2011-540

A Corrected Blade Element Momentum method for Simulating Wind Turbines in Yawed Flow

2011· article· en· W2027596546 on OpenAlex
Michael McWilliam, Stephen Lawton, Shane Cline, Curran Crawford

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

Venue49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition · 2011
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsWind powerBlade (archaeology)Momentum (technical analysis)Marine engineeringFlow (mathematics)Blade element momentum theoryAerospace engineeringAerodynamicsMechanicsStructural engineeringTurbine bladeTurbineEngineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

A new Blade Element Momentum (BEM) model is proposed for yawed wind turbine flows. This method differs from conventional methods in the use of correction factors for the induction. A set of results from potential flow methods is used to define a table of corrections over a wide range of operating conditions and locations within the flow field. The potential flow methods account for the distribution of vorticity in the wake. Applying the resulting corrections give better accuracy than conventional BEM methods. By generating the correction results a priori, the efficiency of the BEM method is preserved. The accuracy of this method and the conventional axial momentum based BEM method are evaluated by comparing results to that of the MEXICO experiment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.033
GPT teacher head0.278
Teacher spread0.245 · 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