Rock mass strength at depth and implications for pillar design
Bibliographic record
Abstract
Construction of infrastructure in deep underground mines depends on an understanding of near wall rock behaviour as well as the ultimate load bearing capacity of confined rock, and thus on a reliable strength criterion for the rock near and far from the excavation. The topic of brittle failing rock i.e. rock failure dominated by tensile crack and fracture propagation even under low overall compressive conditions, is briefly summarised. Recently, it was suggested that the failure envelop for the entire confinement range of brittle rocks and rock masses is distinctly S-shaped. If validated, this impacts engineering problems such as pillar design where both wall instability and confined rock mass stability issues need to be considered. This paper explores the limitations and potential opportunities in pillar design. It is illustrated that current empirical design rules may be flawed and further studies are required to arrive at more economic designs for pillars at depth, or under high stress, and in brittle failing rock masses. When confined in the core of pillars, the rock mass may exhibit superior strength than typically assumed by Mohr–Coulomb or Hoek–Brown failure criteria as it will fail differently than near the wall. As a result, pillar strength may be underestimated based on field observations and if procedures of rock strength back analysis from near wall behaviour are adopted to determine the rock mass strength envelop. This means that the strength of pillars with width to height (W/H) ratios exceeding 1·5 to 2 may be systematically underestimated and may become burst prone, as the core may not yield as anticipated. Consequently, pillar designs based on current empirical rules may be inadvertently conservative and thus not optimal from an economic perspective. This aspect is of particular interest for block cave mines where drawpoint spacing may have a significant impact on cave propagation, recovery performance, and economics.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".