Model-Scale/Full-Scale Correlation in Open Water and Ice for Canadian Coast Guard “R-Class” Icebreakers
Bibliographic record
Abstract
CCGS Pierre Radisson, one of the R-Class icebreakers Model-scale data from the National Research Council of Canada, Institute for Marine Dynamics' water and ice towing tanks for the Canadian Coast Guard's R-Class icebreaker are compared with previous model tests and, more importantly, with three sets of full-scale ice trials data collected in 1978, 1979 and 1991. In open water, good agreement between model-and full-scale was found for bollard tests, and for self-propulsion tests provided a roughness allowance of 0.0008 was used. In ice, good correlation was found with the 1978 tests when the ship was new and there was little snow cover, using a model hull/ice friction coefficient of 0.05. Good agreement with the later tests, 1979 and 1991, was also obtained with somewhat higher model/ice friction coefficients of 0.055 and 0.065. This is attributed to a deteriorating, and hence rougher, full-scale ship hull surface. The model tests showed that a change in friction coefficient from 0.03 to 0.09 causes a doubling of the delivered power. For the full-scale ship, it is suggested that relatively inexpensive localized hull maintenance in the shoulder area, where ice jamming occurs and hence hull/ice friction is important, could improve performance and reduce the chance of structural damage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".