Considering frictional effects on the ice crushing force of a ship-ice impact
Bibliographic record
Abstract
The Popov-Daley method is the current standard for analytically determining ship-ice collision forces and involves converting the available kinetic energy of an impact into ice (or ice + structural) indentation energy. It is part of the current design ice load model in the International Association of Classification Societies (IACS) Unified Requirements for Polar Class Ships (Polar URs) and has seen use in multiple academic studies with ship-ice impact collision scenarios ranging from thick ice and heavy icebreakers or non-ice strengthened ships (NISS) encountering finite floes. The Popov method reduces a six degree of freedom impact between two bodies into a single degree of freedom collision normal to the contact plane by deriving a reduced mass through which the available kinetic energy of the impact is determined. One assumption associated with this method is that frictional effects do not have a substantial effect on impact loads. The present study tests this assumption with a rederivation of the original method that considers frictional effects. Different impact scenarios relevant to both the Polar URs and to more recent studies involving non ice strengthened ships are reviewed, with impact forces calculated by converting the available kinetic energy into ice crushing energy using a process pressure-area relationship as applied by Daley and in the Polar URs. Minimal percent differences in the force levels were found across all tested scenarios. Lower differences were found with scenarios involving smaller ice floes, and the difference level never exceeded 1.5 % across all scenarios tested. This confirms the suitability of the friction related assumption from the original Popov method. An investigation into friction coefficients required for a significant percent difference in force levels resulted in coefficients of as least 0.34, which may occur in different ship collision scenarios but is not realistic for steel-ice contact.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".