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A Numerical Investigation to Identify Dimensionless Parameters for Dual-Rotor Horizontal Axis Wind Turbines

2016· article· en· W2523767275 on OpenAlexaff
Kenny Lee Slew, Michael S. Miller, Edgar Matida

Bibliographic record

VenueJournal of Physics Conference Series · 2016
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsRotor (electric)Dimensionless quantityWind powerTurbineMechanicsControl theory (sociology)Wind speedPhysicsEngineeringAerospace engineeringComputer scienceMeteorologyMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

A numerical study was carried out to identify non-dimensional parameters for dual-rotor horizontal axis wind turbines (DRWTs). Based on some important DRWT parameters such as the rotor speeds, rotor diameters and the distance between the rotors, three dimensionless parameters were derived from the Buckingham Pi theorem. Hypothetical DRWT models were created using geometrically-scaled National Renewable Energy Laboratory (NREL) Phase VI rotor geometry and operating conditions in order to confirm the validity of these parameters. The performance of each turbine was simulated using DR_HAWT, an inhouse prediction tool for single and dual-rotor wind turbines created by the current authors. The variation in normalized output power as a function of the dimensionless parameters suggests that an improved performance of DRWTs can be obtained at lower diameter and gap ratios. The NREL Phase VI rotor equipped with a 5 m geometrically-scaled upwind rotor can generate about 88% of the combined power output of two equivalent single-rotors. In addition, the effect of having an auxiliary upwind rotor reduces the angle of attack along the inboard section of the downwind blade.

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 score0.146
Threshold uncertainty score0.376

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 communication0.0000.001
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 head0.032
GPT teacher head0.270
Teacher spread0.238 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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