Bibliographic record
Abstract
One of the main problems facing mining engineers when dealing with deep, hard rock mines is to prevent and/or reduce rockburst hazard around mine openings. Rockburst is a phenomenon which is characterised by violent rock failure. The current research focuses on the assessment and control of rockbursts in deep, hard rock mines. Strainbursts, or strain-type rockbursts, occur in the vicinity of mine openings and are generally provoked by high stress conditions in a brittle rock mass. A new theory has been developed for the assessment of the potential of violent rock failure by strainburst, in underground hard rock mines. In this theory, the mining-induced energy parameters are used to calculate the so-called burst potential index (BPI). When the BPI reaches or exceeds 100%, the method predicts a burst prone situation. One of the most commonly used methods to control strainbursts in hard rock mines is destress blasting. Motivated by the lack of a dedicated analysis tool to help assess destress blasting, a new, geomechanical model was developed. The technique employs two newly introduced parameters, alpha, a rock fragmentation factor, and beta, a stress dissipation factor, inside the modelled, fractured zone. Implemented in a 3-dimensional finite element code developed by the author, the new model simulates the damage zone induced by destress blasting of a mining face to help evaluate the efficiency of destress blasting. Extensive model verification and parametric studies have been undertaken. The effects of the destress blasting pattern, premining stresses and their orientation, and the two destress blasting factors (rock fragmentation factor, and stress dissipation factor) are studied. The model has been applied successfully to Canadian mine case histories. A detailed case study of a cut-and-fill mine stope involving crown and sill pillar destressing has been carried out. It is shown that the new method can be useful in the assessment of destress blasting in deep drift face development and the crown/sill pillar problems in cut-and-fill mine stopes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".