Analytical Study of an Isotropic Viscoplastic Sea Ice Model in Idealized Configurations
Bibliographic record
Abstract
Abstract Analytic solutions of a mechanical sea ice model are computed in idealized configurations. They are then used to study the properties of this model. It classically assumes that the ice behaves at large scale as an isotropic viscoplastic medium. The plastic regime is characterized by a Mohr–Coulomb yield curve. The flow rule corresponds to the one used in granular mediums and depends on a parameter δ that characterizes the expansion properties of the medium. Using simple model configurations, this study first shows that a sliding of the ice along the coast must be permitted; otherwise, the model generally has no solution when the plastic regime is active. This study then shows that the viscous regime is reached only if the stress remains nearly uniform over a large area. For a stress having no particular properties, the plastic regime acts everywhere. In this case, the compressive stress may reach the maximum value allowed by the model close to the coastline. The extension of the domain where the compressive stress is at its maximum depends on δ and the direction of the forcing field. Over this domain, the ice behaves as a fluid material with a small negative viscosity. Last, the authors found that neither the existence of the solution nor its unicity are guaranteed in this stationary model. This result does not imply that the unicity is lost in the transient problem; it suggests that the evolution of sea ice depends not only on the forcing, but also on the initial conditions or history of the system.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".