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Record W4389541063 · doi:10.17118/11143/20857

H-Darrieus vertical axis wind turbine aerodynamics and aeroacousticsunder different inflow conditions

2023· article· en· W4389541063 on OpenAlexaff
Kartik Venkatraman, Stéphane Moreau, Julien Christophe, Christophe Schram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversité de Sherbrooke
FundersEuropean Commission
KeywordsAerodynamicsInflowVertical axis wind turbineTurbineAerospace engineeringVertical axisAeroacousticsComputational aeroacousticsHorizontal axisWind powerGeologyPhysicsMarine engineeringEngineeringAcousticsMeteorologyStructural engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Abstract: The aerodynamics and aeroacoustics of a scaled model H-Darrieus vertical axis wind turbine (VAWT) with end plates and supporting structures is investigated at its design operational regime. A high-fidelity hybrid Lattice Boltzmann Method/Very Large Eddy Simulation model is achieved and coupled to an in-house aeroacoustic propagation code SherFWH based on the Ffowcs Williams and Hawkings’ analogy for noise prediction. A simulation is first performed under uniform inflow conditions to validate the model with available experimental data. A good agreement is seen between the numerical predictions and the experimental noise spectra for both the tonal peaks at the blade passing frequencies and the broadband noise levels. A second simulation is performed with the VAWT titled by an angle of 20? to study the influence of skewed inflow conditions, which are more representative of a typical urban environment. A 12% decrease in the power coefficient and a 2.3 dB decrease in the overall noise level at a given observer position is seen for the skewed inflow 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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.455

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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