Lessons learnt from a pillarburst at a development heading in one of Vale’s deep mines: a case study
Bibliographic record
Abstract
Over the last decade, Vale’s Sudbury Operations have experienced an increase in the occurrence of significant seismic events. Common contributing elements identified through seismic event investigations include: high quality rock mass conditions combined with high strength and brittle material properties elevated stress levels associated with increased mining depths (up to 2.5 km below surface) unfavourable mining geometries, such as sill and diminishing rib pillars higher extraction ratios, reflecting the maturity of mining operations interaction with seismically active geological structures (joints, faults, dykes and shear zones, etc.). Mitigation strategies focused on these contributing factors have been developed within Vale’s Mining Operations, to manage and control the risks associated with seismicity and rockbursting. This paper presents a unique rockburst event that occurred in a development breakthrough pillar in the 5220 Ramp at Garson Mine that resulted in injuries to two employees. This event triggered a comprehensive investigation to identify the failure mechanism, contributing factors and lessons learned; forming the basis for additional mitigation strategies, focused on minimising and/or preventing future re-occurrence of similar rockbursts. The investigation results are presented in this paper, and the more recent 5300 Level 1210 Level access breakthrough is presented as an example to demonstrate the successful implementation of a new design methodology and process. It is hoped that by sharing this case study with the industry, ground control professionals can be made aware of when rockbursts may occur, and what mitigation strategies can be adopted when a similar mining scenario is encountered at their operations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".