Improving Rock Pillar Stability Guidelines Through Detailed Numerical Investigation
Bibliographic record
Abstract
Abstract Pillar stability guidelines have been presented by numerous authors in the past, based on a combination of empirical observations (mostly visual) from mining applications and simple numerical (elastic or simple continuum plasticity) models. In many cases, the resulting design limits for pillar dimensioning are presented as universal for all rockmass conditions and stress regimes. There have been numerous developments in the past decades in mechanistic classification (brittle spalling, effective continuum rockmass, structural control) and mechanism-appropriate modelling and design metrics. These new tools and paradigms for rockmass behaviour allow for a modelling-based revision of the empirical guidelines from the past century that still form the basis of many performance critical designs. This paper includes the consideration of rockmass deformation and yield (rockmass strength approach), brittle strength, and damage behaviour where appropriate. This paper presents correlations for residual GSI and the effects of Hoek-Brown dilation on pillar behaviour. The investigation includes generating 3D FEM synthetic pillar models with equivalent elastic and plastic continuum.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".