Controlling mechanism of fractures for failure patterns of borehole-containing specimens under cyclic loads
Bibliographic record
Abstract
Gas drainage is one of the main methods for preventing gas accidents in coal mines. However, disturbance induced by coal mining may influence the stability of gas drainage boreholes and thus weaken the gas drainage effect. To solve the problem, loading and unloading experiments with different lower limits of cyclic stress were conducted on specimens containing a hole. At first, the fracture development and the acoustic emission characteristics of the specimens were analyzed. Then, the influences of loading and unloading under different lower limits of cyclic stress on the failure modes of the specimens were studied. Finally, the influencing factors of failure patterns of the hole were discussed. Research results show the effect of loading and unloading with different lower limits of cyclic stress on the degree of deformation and failure of the specimen. The larger the number and the more uniform the fractures around the hole in the specimens are, the larger the shrinkage of the hole at failure. In addition, the loading process of the specimens is divided into a stable period and an unstable period according to the acoustic emission characteristics in the failure process of the specimens. Research results help to determine failure modes and failure patterns of gas drainage boreholes under disturbance induced by different coal mining conditions in advance according to development characteristics of fractures around boreholes and then ascertain gas drainage states of boreholes. This prevents the occurrence of gas accidents and provides theoretical support for the safe production of coal mines.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".