Modeling Sea Ice fracture at very high resolution with VP rheologies
Bibliographic record
Abstract
Abstract. Recent high resolution pan-Arctic sea ice simulations show fracture patterns (Linear Kinematic Features – LKFs) that are typical of granular materials but with intersection (fracture) angles wider than those observed from high-resolution satellite images (with a modal value of θ = 20°). In this article, We investigate the mechanism of formation and parameter dependencies of ice fracture in simple numerical bi-axial test on a 8 km x 25 km ice floe at an unprecedented resolution of 25m for two different yield curves: an elliptical (VP) and a Coulombic yield curve both with normal flow rule. In the standardVP model, the simulated angle of fracture is θ = 33.9°, compared to 20° in observations. The dependence of the angle of fracture on the ice shear strength is also contrary to that of typical granular materials with larger angle of fracture for higher shear strength – think of a wet sand castle with steeper walls than a dry sand castle. In this model, the divergence along the fracture lines (or LKFs) is entirely dictated by the ice shear strength used in the model with high shear strength resulting in convergence along LKFs and low shear strength resulting in divergence along LKFs. This is again contrary to typical granular materials where divergence (or dilation) is linked with the orientation of contacts normals that oppose the flow with divergence present for larger shear resistance and convergence for lower shear resistance. Moreover, the angle of fracture depends on the confining pressure in the uni-axial test with more convergence as the confining pressure increases, again contrary to granular material that have an angle of fracture that is independent of the confining pressure. We note that all three behaviors of the VP model are linked with the use of an associative (normal) flow rule. In the Coulombic model, the angle of fracture is smaller (θ = 23.5°), but the solution is unstable when the compressive stresses are too large because of the discontinuity between the straight limbs of the yield curve and the elliptical capping. Our results show that while the VP model gives angles of fracture that are visually correct, the bias in the magnitude of the angle of fracture and the physical dependencies of the angle of fracture on mechanical strength parameters and stress fields couple the sea ice mechanical strength parameters, the sea-ice drift, sea-ice deformation (strain-rate) field in an inconsistent way. We consider this evidence to move away from the elliptical yield curve and associative (normal) flow rule, a deformation law that is not applicable to pressure-sensitive and dilatant granular material such as sea ice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".