Comparison of DP Performance Prediction Techniques for Scaled Models
Bibliographic record
Abstract
Utilization of Dynamic Positioning (DP) systems for offshore exploration and production of hydrocarbons is increasing due to the need to exploit deeper water depths, where mooring becomes less feasible. In conducting analysis or predictions for DP System performance, there are two common techniques used: Either an experimental investigation at reduced scale using a simplified mooring system without thrusters; or, a similarly scaled experiment using active DP thrusters. This paper identifies differences in the DP system performance estimates for each method by assessing the same system in identical wind–wave environments. Experiments were completed using a 1:40 scale model of a typical 99,000t monohull drillship equipped with an active DP system consisting of six azimuthing thrusters. These experiments were repeated with the vessel unpowered on two mooring systems with different stiffnesses. A comparison of system performance predictions provided by each method is presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".