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Study of the near wake of a wind turbine in ABL flow using the actuator line method

2014· article· en· W2007177028 on OpenAlexaff
Janani Priyadharshini Veeraperumal Senthil Nathan, M. A. Bautista, C. Masson, Louis Dufresne

Bibliographic record

VenueJournal of Physics Conference Series · 2014
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsWakeTurbulenceReynolds-averaged Navier–Stokes equationsMechanicsPhysicsTurbineTurbulence kinetic energyFlow (mathematics)K-epsilon turbulence modelBoundary layerPlanetary boundary layerMeteorologyGeologyAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

The main goal of this study is the comparison of the near wake generated by an actuator line immersed in three different flows. A hybrid RANS-LES method is used to analyze the behaviour of the near wake in an atmospheric boundary layer. Then these results are compared to two idealized flow situations commonly found in the literature, such as irrotational flow and homogenous isotropic turbulence. In order to achieve this, a validation of the homogenous isotropic turbulence is conducted. The simulation results and the generated turbulence are compared with respect to the turbulence intensity and the integral length scale of the flow field. Finally to visualise the impact of the different flow conditions on the near wake of a wind turbine, the mean velocities, Reynolds stresses and energy spectra are compared.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.280
Teacher spread0.245 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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