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Record W1600631709 · doi:10.1109/acc.2015.7171904

Control-oriented physics-based models for floating offshore wind turbines

2015· article· en· W1600631709 on OpenAlexaff
Jeffrey R. Homer, Ryozo Nagamune

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsUniversity of British Columbia
FundersNational Renewable Energy Laboratory
KeywordsTorqueControl theory (sociology)Offshore wind powerTurbineWind powerBlade pitchNonlinear systemRotor (electric)Generator (circuit theory)DrivetrainComputer scienceEngineeringControl engineeringPhysicsControl (management)Aerospace engineeringMechanical engineeringPower (physics)

Abstract

fetched live from OpenAlex

This paper proposes a general control-oriented non-linear model for floating offshore wind turbine systems. It contains as many as six platform degrees of freedom as well as the rotor degree of freedom, and can account for full field wind and wave disturbances. Additionally, it accepts individual blade pitch, generator torque and yaw control inputs. The model is derived by assuming that the entire structure behaves as a single rigid body, under the influence of various forces and torques. Furthermore, it can be linearized analytically, making the wave disturbance matrix obtainable. We validate the proposed nonlinear model with advanced simulator FAST. Finally, we derive a simple LPV model from the proposed non-linear model.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.219
Teacher spread0.188 · 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
GenreMethods

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

Citations12
Published2015
Admission routes1
Has abstractyes

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