Study of rock burstability with mechanical property testing and microscopic image analysis
Bibliographic record
Abstract
Rockbursts are considered some of the most dangerous phenomena that occur in underground mines. Severe rockbursts can result in injuries, equipment damage, and even fatalities. Other devastating impacts of rockbursts are increased levels of anxiety by the mine operators following a damaging rockburst, delayed production due to rehabilitation work, and economic losses. Therefore, rockburst prediction and control is a key element to the success and safety of underground mining operations. This study concerns itself with the identification of strainburst potential of hard rocks in underground mines. Strainburst phenomena are associated with strong and brittle rocks that exhibit sudden and violent energy release at failure. First, a comprehensive literature review of the rock burstability criteria is carried out and the most common criteria used in the literature are retained for the study. A laboratory investigation program for both mechanical tests and microstructure analysis with optical microscopy was designed and implemented. Rock cores from two operating Canadian mines were acquired for the purpose of examining their burstability. They are basaltic komatiite and norite. A total of 67 mechanical property tests were conducted including uniaxial compressive strength, Brazilian tensile strength, and load-unload. The latter test was conducted to determine the strain energy index of the rock – a well-known criterion for the prediction of strainburst potential. The results indicate that basaltic komatiite shows moderate to high burstability whereas norite shows consistently high burstability. To confirm the trends, 20 rock slices were then prepared for optical microscopy and image analysis software. The results show that basaltic komatiite contains fine grains of carbonate and phyllosilicate minerals that make the rock weak and ductile. On the other hand, the results for norite show high content of k-feldspar and plagioclase which are strong and large-grained, thus supporting the finding of mechanical tests that it is highly burstable. This study shows that the combination of microscopy with mechanical testing proves to be useful in assessing rock burstability
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| 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".