Simulations of the StationKeeping of Drillships Under Changing Direction of Ice Movement
Bibliographic record
Abstract
Abstract The ability of a drillship to maintain its heading to face oncoming pack ice is crucial under situations involving changes in pack ice drift direction. The performance of a vessel employing a Thruster-Assisted Mooring (TAM) system under such conditions is examined in this paper. Numerical simulations were used to determine the stresses and deformations within the moving pack ice cover, as well as the response of a drillship with characteristics similar to published information on Stena's DrillMAX. A turret mooring system is assumed to resist surge and sway direction offsets, but provides no restoring moment to vessel's yaw. In such system, thrusters would be used to provide damping and to apply the corrective moment that controls the heading of the vessel. The pack ice cover is assumed to consist of managed floes of sizes ranging from 30 m to 50 m, and with a uniform thickness of 1 m. The ice cover moves against the vessel at a steady velocity of 0.5 m/s. Simulations start with the vessel at a heading inclined to the oncoming ice direction. The simulations predict the evolution of the distributions of ice thickness and pressures, ice forces and moments, as well as the response of the vessel. Test cases examined a range of values of the initial heading of the vessel and limits on available yaw moment that can be generated by the thrusters. The results illustrate the manner in which the vessel can correct its heading, and give the corresponding offsets, ice forces and moments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".