Observations and analysis of incidences of rockburst damage in underground mines
Bibliographic record
Abstract
[Truncated abstract] This thesis deals with the topic of rockburst damage in hard rock, mechanised underground mines. Specifically, given a seismic event occurs at or near an excavation boundary, what factors specific to the characteristics of that excavation determine whether or not rockburst damage occurs and the severity of that damage? These findings were used to develop a probabilistic and empirical based system for assessing the rockburst damage potential of an excavation. An extensive literature review was undertaken to identify the current state of understanding of the rockburst problem, as well as determining shortcomings in the understanding of the rockburst damage potential of underground excavations. The review showed that there was no widely adopted or effective method of determining the likelihood and severity of rockburst damage. A large catalogue of rockburst case histories was collected. The catalogue comprised of 254 instances of rockburst damage from 13 hard rock, metalliferous, mechanised underground mines in Australia and Canada. The mines cover a range of commodities, geological conditions, mining methods and ground support practices. Through preliminary assessment of these case histories it was apparent that certain excavation specific factors contributed to the occurrence and severity of rockburst damage and were common across the different mine sites. It was found that for a given magnitude seismic event at a given distance from an excavation (that is, a characteristic peak particle velocity) there is a significant amount of variation in the amount of rockburst damage done which is dependent on site specific factors at the damage site. The literature review identified that there was limited data available on the in situ performance of complete ground support systems when subjected to dynamic loading.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| 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".