Mohr-Coulomb yield curve and non-normal flow rule for sea ice viscous-plastic models
Bibliographic record
Abstract
Deformation in sea ice takes the shape of narrow lines of high deformation, called the Linear Kinematic Features or LKFs. The distribution of intersection angles between LKFs indicates that the yield curve of sea ice is closer to the shape of a Mohr-Coulomb criterion than the commonly used elliptical yield curve, and that the flow rule of sea ice is most probably not normal to the yield curve. Thus, having Mohr-Coulomb yield curves in sea ice viscous-plastic models could improve the orientation and localization of LKFs in high-resolution sea ice models. In this work, we define multiple implementations of the Mohr-Coulomb yield criterion with different flow rules and test them in uniaxial compressive tests. We observe that the intersection angles are not the same as we expect from theory and previous experiments with the elliptical yield curve. To further the investigation, we define new rheologies with different yield curves and plastic potentials to study the effect of non-normal flow rules with different yield curve shapes, with the goal to finally be able to define a Mohr-Coulomb yield curve and flow rule that accurately models the creation of LKFs and their intersection angles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".