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Record W2977237751 · doi:10.5539/jsd.v12n5p84

Comparing the Effect of Rotor Tilt Angle on Performance of Floating Offshore and Fixed Tower Wind Turbines

2019· article· en· W2977237751 on OpenAlexvenueno aff
Wongsakorn Wisatesajja, Wirachai Roynarin, Decha Intholo

Bibliographic record

VenueJournal of Sustainable Development · 2019
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsnot available
FundersRajamangala University of Technology Thanyaburi
KeywordsTurbineMarine engineeringTilt (camera)Wind powerRotor (electric)TowerAnemometerWind speedEnvironmental scienceAngle of attackRelative windOffshore wind powerMeteorologyMechanicsEngineeringStructural engineeringPhysicsAerospace engineeringAerodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

The development of Floating Offshore Wind Turbines (FOWTs) aims to improve the potential performance of the wind turbine. However, a problem arises due to the angle of tilt from the wind flow and the floating platform, which leads to a vertical misalignment of the turbine axis, thereby reducing the available blade area and lowering the capacity to capture energy. To address this problem, this paper seeks to compare the influence of the rotor tilt angle on wind turbine performance between fixed tower wind turbines and FOWTs. The models used in the experiments have R1235 airfoil blades of diameter 84 cm. The experiment was analyzed using a wind tunnel and mathematical modelling techniques. Measurements were obtained using an angle meter, anemometer and tachometer. Testing involved wind speeds ranging from 2 m/s to 5.5 m/s, and the rotational speeds of the two turbine designs were compared. The study found that the rotational speeds of the FOWTs were lower than those of the fixed tower turbines. Moreover, at tilt angles from 3.5° – 6.1° there was a loss in performance which varied between 22% and 32% at different wind speeds. The tilt angle had a significant effect upon FOWTs due to the angle of attack was continuously changing, thus altering the optimal position of the turbine blades. This changing angle of attack caused the effective area of the rotor blade to change, leading to a reduction in power output at suboptimal angles. The study finally makes recommendations for future studies.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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 designObservational
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

Citations4
Published2019
Admission routes1
Has abstractyes

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