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Record W4313296714 · doi:10.53907/enpesj.v2i2.65

A review of Stall Delay Models and their Application on Hybrid Methods

2022· review· en· W4313296714 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.

Bibliographic record

VenueENP Engineering Science Journal · 2022
Typereview
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsStall (fluid mechanics)AerodynamicsComputer scienceTurbineActuatorWind powerControl theory (sociology)Aerospace engineeringEngineeringControl (management)

Abstract

fetched live from OpenAlex

This paper is a review on the stall delay phenomenon that Horizontal Axis Wind Turbines (HAWT) encounter under typical flow conditions and its numerical modelling. Aerodynamic performance predictions of HAWT have been often carried out through Computational Fluid Dynamics method with the combination of the concept of actuator disk i.e. hybrid method. For this purpose, the hybrid method is presented in details together with the numerical modelling of such stall delay phenomenon. Despite modern wind turbines are equipped with sophisticated control systems for avoiding stall, nevertheless, stall is still inevitable in the near root region of the rotor blade. This paper focuses on recent research development materials which have been undertaken on the stall delay phenomenon where the engineering models (stall delay models) of the literature being presented and criticized based on the predictions obtained from the NREL Phase VI wind turbine experiments.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.055
GPT teacher head0.350
Teacher spread0.295 · 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