An analytically derived solution for the time history of a ship-ice impact
Bibliographic record
Abstract
The Popov-Daley method is a closed form analytically derived model used for calculating contact forces of a ship-ice impact. It consists of determining the available kinetic energy of the ship-ice system which is then dissipated into indentation energy. This method has been applied in multiple areas, with the International Association of Classification Societies (IACS) Unified Requirements for Polar Class Ships (Polar URs) using the Popov-Daley method as part of its design ice load model, assuming that all energy is dissipated through ice crushing, whereas other studies involving non-ice strengthened ships allow for structural deformation and thus consider both ice and structural indentation energies. More recently, the Popov-Daley method has seen use in multiple academic studies where its application over a period of time is desired, but a solution for the time – history derived from the underlying energy balance equations does not currently exist. With this in mind, a method for analytically solving the time history of a Popov-Daley style ship ice collision model has been developed, with equations derived for the indentation depth – time relationship as well as for the total time of the collision using the same assumptions employed in the Polar URs. The proposed models were found to be in very good agreement with numerical and preliminary experimental results. Applications of the models and further necessary validation work are both discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".