Mooring and hydrostatic restoring of offshore floating wind turbine platforms
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".