Experimental Study of Dynamics During Crushing of Freshwater Truncated Conical Ice Specimens
Bibliographic record
Abstract
Ice crushing dynamics in ice structure interactions can result in hazardous vibrations and potentially damaging loads on offshore structures. Ice cone crushing experiments were conducted in the lab to characterize loading and dynamics processes for compressive failure. The indentation rate, temperature and shape of the ice specimens were varied in control tests so that the sensitivity of the resultant dynamic ice load frequency and amplitude could be determined. The results indicate that all control variables had a marked effect on both the frequency and amplitude of load fluctuations. Indentation rates varying from 0.1 mm/s to 10 mm/s and ice taper angles from 13° to 30° had drastic effects. The effects of temperature also demonstrated variations in force, pressure and dynamic behavior. In addition to load measurements, video was used to observe failure mechanisms and in particular spalling and crushing. In the present paper observations are described, though a thorough quantitative assessment has been published elsewhere. Tactile pressure sensors were also used in the experiments, allowing for the correlation of loads and processes to pressure distributions. Finally, the forensic examination of crushed specimens also provided insights into the behavior of ice under various compressive failure scenarios. On the surfaces of intact specimens and revealed within through cross-polarized views of thin sections were signs of ice damage and recrystallization zones of varying extents. The effects of the variables on the dynamic processes and failure behaviors are discussed.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".