Modelling of ice crushing with Material Point Method
Bibliographic record
Abstract
AbstractIce crushing has been a challenging process to model because of the large number of particles and fragments, which present computational difficulty, as well as the non-trivial constitutive behavior of the material. The Material Point Method (MPM) is a promising modeling technique in situations with high deformations where the material transitions from solid to granular. A continuum damage MPM has been developed to model dynamic ice crushing under indentation. We reproduce the significant experimentally observed phenomena, such as the localized damage near the indenter, ejection of fine particles, spalls, and cracks in the solid part of the sample. Moreover, the modelling approach reproduces important features of ice-structure interaction, most notably the formation and evolution of high-pressure zones. Our approach can potentially contribute to assessing risks in ice-structure interaction, iceberg keel impacts on subsea pipelines, ice-pipe-soil interactions, and other applications.
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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 | 0.000 | 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) | 0.017 | 0.002 |
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; both teacher heads agree on what is shown here.
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".