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Record W4389584952 · doi:10.17118/11143/20942

Numerical flutter analysis of a horizontal axis wind turbine blade withrotational tower base

2023· article· en· W4389584952 on OpenAlexaff
Saeid Fadaei, Fred F. Afagh, Robert Langlois, Abbas Mazidi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsFlutterHorizontal axisTowerBlade (archaeology)Base (topology)TurbineVertical axisTurbine bladeMarine engineeringGeologyAerodynamicsAerospace engineeringStructural engineeringEngineeringGeometryMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract: In this study, the flutter occurrence of a blade of a horizontal axis wind turbine (HAWT) with rotation of the tower base is investigated. The wind turbine tower is modelled with rotation about three axes: pitch, roll, and yaw. The blade is modelled as a non-uniform Euler-Bernoulli beam in bending and torsion, which can experience large deflections. The discretized form of the aeroelastic governing equations of the blade is obtained by combining blade element momentum (BEM) theory and geometrically exact beam theory (GEBT). As a case study for the obtained analytical model in this paper, the physical and geometrical properties of the NREL 5 MW reference wind turbine blade are considered. In this regard, for each property, a mathematical function that has been fit to the series of data points corresponding to the NREL 5 MW turbine blade is constructed and used in the aeroelastic governing equations. To validate the obtained numerical model of an HAWT blade, the modal response of the blade is compared to the response obtained for a representation of the blade developed using CAD and modelled with the ABAQUS software suite. Good agreement between natural frequencies and mode shapes is observed. Results are presented for operational wind turbine rotors. Results show the significant effect of turbine tower rotation, due for example to wave action on a floating wind turbine base, on the aeroelastic stability of the blades. Further, it is shown that coupled motion of the platform as a rigid body combined with rotor angular velocity can lead to flutter instability at low wind speeds.

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 categoriesInsufficient payload (model declined to judge)
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 score0.312
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.231
Teacher spread0.220 · 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.

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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