Turning and stopping of a ship with twin Z-drive thrusters
Bibliographic record
Abstract
The superior manoeuvrability of Z-drive equipped vessels is well known, though the comprehensive manoeuvring characteristics are seldom quantified. This paper presents the results of a sea trial on a 55 m ship equipped with twin Z-drive propulsion. Three manoeuvre types were conducted: turning circles, effective turning tests, and crash stops. Each were done for a range of ship speeds and thruster azimuth angles. For the turning circles, steering modes using both a single thruster and dual thrusters were also examined. The effective turning tests were used to determine the best or best-compromise thruster angles to achieve a high rate-of-turn with the least loss of ship speed. The crash stop tests investigated two different stopping methods: full reverse thrust and stopping by swinging the thrusters to 90°. • Manoeuvring sea trials were performed on a ship with twin Z-drive thrusters. • The data was analysed to quantify the turning and stopping metrics of the ship. • Results show performance changes based on helm configuration and stopping method.
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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 | 0.001 |
| 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 | 0.001 |
| 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".