Numerical Simulation of Ship Maneuvering in Pack Ice
Bibliographic record
Abstract
This paper presents preliminary results from a computer program for simulating ship maneuvering in ice covered waters. The program is derived from two programs, Ship Maneuvering Laboratory (SML) and a discrete element numerical modeling program (DECICE). SML is an in-house code developed by Oceanic Consulting Corporation for simulating ship maneuvering in open water. It is based on a ship maneuvering model originally developed by the Japanese mathematical maneuvering group (MMG). DECICE is a discrete element method which was developed by INTERA Technologies and is used to calculate the ice loads on the ship and the interactions between ice pieces. The paper presents a summary of the mathematical methods used together with the results of some case studies for ships EXM004, PSM004 and Esso Osaka Tanker. These computer predictions include turning circle and Zig-Zag maneuvers. Comparisons and discussion of the simulated results between cases with and without ice are also provided.
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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 | 0.000 |
| 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".