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Record W2058800445 · doi:10.1260/0309524043729958

On the Rotor Effects upon Nacelle Anemometry for Wind Turbines

2004· article· en· W2058800445 on OpenAlexaff
Arezki Smaïli, Christian Masson

Bibliographic record

VenueWind Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsNacelleAnemometerTurbineRotor (electric)TurbulenceMarine engineeringMechanicsWind powerAerospace engineeringMeteorologyComputational fluid dynamicsEnvironmental scienceEngineeringPhysicsMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The objective of this paper is to study the typical atmospheric turbulent flow around the rotor and nacelle of a HAWT, in order to (i) investigate the impact of the turbine's rotating blades on the flow field over the nacelle, i.e. the rotor-nacelle interaction; (ii) assess the appropriate anemometer location on the nacelle, and therefore (iii) establish the relationship between wind speed measured near the nacelle and free stream wind speed. The paper presents a numerical method for investigating the effects of rotating rotor blades on the nacelle anemometry of a horizontal axis wind turbine (HAWT). The flow field around the turbine and nacelle is described by the Reynolds averaged Navier-Stokes equations. The k – ε model has been chosen for the closure of time-averaged turbulent flow equations. The rotor is modelled using the actuator-disk concept. The simulation results were performed using a commercial wind turbine rated at 750kW. In general, good qualitative agreements have been found, supporting the validity of the proposed method. However, quantitatively, the accuracy of the simulation results should be confirmed before any use is made in power performance testing.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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

Citations34
Published2004
Admission routes1
Has abstractyes

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