Effects of Hull Geometry and Tightness of Turns on Ship Maneuverability: An OSIS-IHI Simulation
Bibliographic record
Abstract
Abstract OSIS-IHI (Ocean Structure Interaction Simulator – Ice-Hull Interaction) is a ship maneuvering in ice modeling software developed at OCRE for a marine simulator and ship performance assessment applications. A series of OSIS-IHI simulations is conducted to explain the maneuvering behavior observed of the USCGC Polar Icebreaker indicative design previously tested at the centre. The simulation is conducted with the original and a modified version of the USCGC Icebreaker Healy. The Icebreaker USCGC Healy was equipped with doublescrew conventional propellers. The hull geometry of the OSIS-Healy model is appropriately modified to mimic the hull form of two indicated design versions in question and its propulsion units replaced by twin pods prior to studying its maneuverability in order to shed light on the apparently poor maneuvering performance of the podded version of the indicative design. The modified version extends the mid-body leaving just 7.5 % of hull that constitutes the stern section. It is hypothesized that the extended mid-section cost large resisting moment against turning due to the increase of ice breaking at the aft shoulder and mid-body. This hypothesis is validated numerically to explain the poor maneuverability exhibited by the extended mid-body design, based on consideration of ice-hull interaction geometry and basic mechanics of ice breaking as well as existing anecdotal test evidences. This paper presents result of the simulation to explore effects of hull geometry and tightness of turns on ship maneuverability. Important insights gained are summarized and recommendation for further work given.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".