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Record W2587268859 · doi:10.1109/tcst.2017.2654420

Physics-Based 3-D Control-Oriented Modeling of Floating Wind Turbines

2017· article· en· W2587268859 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsUniversity of British Columbia
FundersNational Renewable Energy LaboratoryNatural Sciences and Engineering Research Council of CanadaInstitute for Computing, Information and Cognitive Systems
KeywordsDrivetrainTurbineTorqueOffshore wind powerWind powerMarine engineeringSoftwareEngineeringControl engineeringControl theory (sociology)Aerospace engineeringComputer sciencePhysicsControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

This paper presents a physics-based control-oriented model for general floating offshore wind turbines that contains as many as six platform degrees of freedom (DOFs) and two drivetrain DOFs. The model is derived from the first principles, and therefore, can be manipulated by its real physical parameters while maintaining accuracy across the highly nonlinear operating range of floating wind turbine systems (WTSs). Forces and torques generated by wind and wave disturbances are derived for a baseline 5-MW wind turbine on a semisubmersible platform. The proposed model is validated against advanced simulation software FAST, and shown to be accurate at predicting major dynamics of the floating WTS.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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