Observation of microscopic damage accumulation in brittle solids subjected to dynamic compressive loading
Bibliographic record
Abstract
Dynamic failure of brittle materials is a fundamental physical problem that has significantly impacts to many science and engineering disciplines. As the first and the most important step towards the full understanding of this problem, one has to observe dynamic damage accumulation in brittle solids. In this work, we proposed a methodology to do that and demonstrated it by studying the dynamic compressive damage evolution of a granitic rock loaded with a modified split Hopkinson pressure bar system. To ensure consistency of the experimental results, we used cylindrical rock samples fabricated from the same rock core and subjected them to identical incident loading pulse. Using a special soft recovery technique, we stopped the dynamic loading on the samples at different strain levels, ranging from 0.3% to 1.4%. Therefore, we were able to recover intact samples loaded all the way to the post-peak deformation stage. The recovered samples were subsequently examined with X-ray micro-CT scanning machine. Three dimensional microcrack network induced by the dynamic loading was observed and the evolution of microcracks as a function of the dynamic loading strain was obtained.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".