Anisotropy in fracture toughness of shale and coal under dynamic loading
Bibliographic record
Abstract
Notched semi-circular bend (NSCB) samples are prepared with different bedding angles and subjected to dynamic loading by a modified split Hopkinson pressure bar (SHPB) system. The static fracture toughness (SFT) of shale or coal increases linearly with the bedding angle. Under similar loading rates, the dynamic fracture toughness (DFT) of shale increases as the bedding angle rises. However, the DFT of coal is much discrete. The DFT of shale or coal increases with loading rate increasing. DFT is much higher than SFT. For shale, there is almost a linearly positive correlation between DFT and loading rate, while for coal, there is a logarithmic relationship. All values of coal are much smaller than that of shale. As the loading rate increases, the effect of bedding angle on DFT attennuates. Notably, for bedding angle of 45°, the cracking mode of coal is more easily affected by bedding plane, than for other angles.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".