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Record W4402438541 · doi:10.11159/htff24.136

EA 3D-DDES Numerical Simulation of Jet Blowing as a Power Enhancement Technique Applied to a Wind Turbine with S809 Profile

2024· article· en· W4402438541 on OpenAlexvenueno aff
Giacomo Tosatti, Luca Manni, Ivano Petracci

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
Fundersnot available
KeywordsTurbineWind powerJet (fluid)Aerospace engineeringComputer simulationPower (physics)MechanicsAerodynamicsComputer sciencePhysicsEnvironmental scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The aerodynamic performance of the NREL Phase VI wind turbine is investigated through the use of the blade element momentum (BEM) theory and computational fluid dynamics (CFD).The baseline configuration, consisting of an S809 airfoil, is modified to employ trailing edge blowing technology, an active circulation control technique known as Coanda Jet.Calculations are performed via 3D Delayed Detached Eddy Simulation (DDES) to solve the three-dimensional flow structures over the airfoil correctly.A preliminary campaign of simulations is first conducted for a wide range of angles of attack from = 0 to = 20 on an airfoil with chord c = 0.482 m with a wind speed equal to 29.3 m/s, which corresponds to the chord at 75% of the blade radius and the relative wind velocity it experiences respectively.Results are confronted with experiments to validate the model.Once mesh fidelity is proven, five different radial positions along the blade are considered and simulations are performed with and without jet blowing to prove its efficiency.Results show that lift and thrust force both increase, enhancing net power generated by the wind turbine, which is calculated via BEM.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.675

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

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