Side-viewing high-speed video observations of ice crushing
Bibliographic record
Abstract
Rectangular thick sections (1 cm thickness) of lab-grown mono-crystalline ice have been confined between two thick Lexan plates and crushed at -10°C from one edge face at a rate of 1 cm/s using a stainless steel platen (1 cm thickness) inserted between the plates. The transparent Lexan plates permitted side viewing of the ice behavior during crushing and the visual data were recorded using high-speed video. An in-plane fracture occurs in the ice sample early in the tests and expands from the platen/ice contact area as load increases. Ice on one side of the in-plane fracture experiences shattering ands pulverization while the ice on the other side remains intact but melts at the platen/ice contact where the pressure is high (~40 MPa). The continuous production and flow of liquid at high pressure in a thin layer at the intact ice/platen interface was strikingly evident and most of the load was supported in this zone. While some spalls did occur at the intact ice contact zone, cyclic spalling that normally occurs in the ice crushing experiments was suppresses due to the unusual confinement arrangement. The crushing on one side of the in-plane fracture and melting on the other side occurred continuously at the nominal platen penetration rate for most of a test, however, when spalls did occur the relative platen/ice penetration rate was momentarily higher due to the release of elastic energy in 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".