Spherical Indentation Tests on Confined Ice Specimens at Small Scales
Bibliographic record
Abstract
A recent series of small-scale ice indentation tests was conducted as a continuation of previous series, to cover additional strain rates and indentor sizes, and to test the effect of scaling. Tests using indentors 10, 20, 40 and 70 mm in diameter attached to a very stiff structure were carried out at indentation rates over three orders of magnitude, while scaling indentation rate with indentor diameter. Slow rates resulted in creep-like response and deep and wide damage zones. As indentation rate was increased, sawtooth loading and random failure activity were observed, together with a thin layer of microstructurally modified ice beneath the indentor. This latest test series also included indentation tests with a flexible beam apparatus, with the aim of generating locked-in vibrations. It was determined from previous tests that indenting at much faster rates was necessary to produce lock-in with such an apparatus. For this series, two new beam apparatus of differing stiffness and variable natural frequency were fabricated; the beams were designed in a manner that enabled control and testing of the outcome of varying these factors independently. Tests were conducted with either one or two indentors attached. The typical sawtooth behaviour occurred at lower indentation rates, progressing at higher rates into lock-in activity, which occurred over a range of speeds for both beams. The frequency of lock-in vibrations was found to be lower than the structure’s natural frequency, and to increase with indentation speed over the lock-in range. The ice load on the indentor during lock-in activity appears more ‘cusp’ shaped, rather than the assumed sawtooth.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".