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Record W2003883001 · doi:10.1088/1742-6596/75/1/012037

Recent advances in modeling of wind turbine wake vortical structure using a differential actuator disk theory

2007· article· en· W2003883001 on OpenAlexafffund
Christophe Sibuet Watters, Christian Masson

Bibliographic record

VenueJournal of Physics Conference Series · 2007
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsÉcole de Technologie Supérieure
FundersNational Renewable Energy LaboratoryNatural Sciences and Engineering Research Council of Canada
KeywordsWakeAerodynamicsTurbineLift (data mining)Aerospace engineeringInflowMechanicsVortexActuatorLift-to-drag ratioAngle of attackDragEngineeringMarine engineeringControl theory (sociology)PhysicsComputer science

Abstract

fetched live from OpenAlex

This paper presents the recent developments of a new CFD-based method aimed at predicting wind turbine aerodynamics, where velocity and pressure discontinuities are used to model the vortical system that creates lift on the turbine blades. To illustrate the ability of the present model to predict induced wake effect, the case of the taper wing is thoroughly analyzed and effects of both domain discretization and convection scheme are presented. Results are mitigated regarding predicted performance of induced drag, but accurate induced and upstream flow angles values are obtained. The method is even shown to be a useful calculator for the relationship between inflow angle measured upstream and effective angle of attack of a wing section. Interesting results for the NREL phase VI rotor have been obtained showing improvement of the method upon actuator-disk approach in handling tip vortices effect on the blade aerodynamics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations13
Published2007
Admission routes2
Has abstractyes

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