Evaluation of ice island ‘footloose’ calving events using finite element analysis
Bibliographic record
Abstract
Abstract Ice islands, massive tabular icebergs, are known to fracture as they drift. The footloose mechanism occurs when a large protuberance, known as a ram, develops along the submerged edge of the ice island and induces a buoyancy-driven bending stress. This study investigates the relationship between rams and footloose fracture using finite element models of ice islands with simulated underwater rams. Geospatial polygons of ice islands, derived from remote sensing imagery, were used to create three-dimensional shapes of ice islands at two thicknesses and with various ram sizes. Then, the location of maximum stress and fractures were predicted using finite element analysis (FEA) and the results were compared to remote sensing observations of the actual fractured pieces that calved from each of the 26 modelled ice islands. Accurate simulations of calving were achieved when a synthesized ram was placed along the ice island edge where the calving was observed. An empirical model was developed to predict the magnitude of stress from various ram sizes and shapes. The predictive ability of this empirical model suggests that ice island calving models can be improved and combined with drift forecasting models to help mitigate risks to offshore infrastructure and seafaring vessels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".