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Record W2006255641 · doi:10.1109/oceans.2014.7003269

Mooring and hydrostatic restoring of offshore floating wind turbine platforms

2014· article· en· W2006255641 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsStiffnessBARGEMooringSparMarine engineeringHydrostatic equilibriumOffshore wind powerTurbineEngineeringSurgeStructural engineeringStiffness matrixMechanical engineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper investigates the restoring stiffness of the main platform concepts proposed for offshore floating wind turbine (FWT) systems; namely, barge, spar, tension leg platform (TLP). The overall system stiffness is partly due to the hydrostatics, and partly due to mooring. The hydrostatic stiffness matrix is formulated using the linear hydrostatic approach that assumes small platform rotation. A new analytical form of the mooring stiffness matrix for a taut-leg platform is presented and subsequently used to formulate the TLP mooring stiffness. While a numerical approach, is used for the other two platform types. The hydrostatic and mooring stiffness coefficients for the surge, sway, heave, roll, pitch and yaw degrees of the freedom (DOF) are computed for the different types of platforms. For each DOF, the magnitude of stiffness from both hydrostatics and moorings are compared.

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 categoriesnone
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 score0.153
Threshold uncertainty score0.353

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 communication0.0000.000
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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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

Quick stats

Citations8
Published2014
Admission routes1
Has abstractyes

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