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Numerical Study of Flow Around Iced Wind Turbine Airfoil

2012· article· en· W2334811876 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEngineering Applications of Computational Fluid Mechanics · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversité du Québec à RimouskiUniversité de MontréalPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsAirfoilAngle of attackAerodynamicsStreamlines, streaklines, and pathlinesTurbineNACA airfoilAerospace engineeringLift coefficientMarine engineeringLift-to-drag ratioLift (data mining)FluentDragPressure coefficientGeologyMechanicsTurbulenceComputational fluid dynamicsEngineeringPhysicsComputer scienceReynolds number

Abstract

fetched live from OpenAlex

This investigation analyzes the impact of ice accretion on the aerodynamic coefficients of a wind turbine airfoil. Three blade sections located at different radial positions were analyzed. Numerical simulations were conducted over a two-dimensional clean and ice-accreted NACA 63–415 airfoil at various angles of attack. The results for pressure, lift, and drag coefficients were inspected at an angle of 13° for which experimental data were available. The streamlines around the clean and iced airfoil were also inspected, in order to evaluate the ice impact on lift and drag. The simulations were carried out using the commercial package FLUENT, and turbulence was addressed with the SST k - ω) model.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.524
Threshold uncertainty score0.483

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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