Rockbursts Characterization in the Merensky Reef: A Case Study in Siphumelele Platinum Mine, South Africa
Bibliographic record
Abstract
ABSTRACT Rockbursts have remained one of the most serious and least understood problems facing deep mining operations, claiming the lives of thousands of mine workers. Despite many technical advances, rockburst continues to pose a significant risk in deep platinum mines of South Africa as they damage excavations, mining equipment and infrastructures, delay production and cause injuries or even deaths of mining personnel. We analyzed the source mechanisms of large mining-related seismic events (ML1.0 − 2.5) that caused damage to stopes in Siphumelele Platinum Mine. This study attempts to mitigate the risk of rockburst by integrating rock mass complexities (high stress, complex structural geology, mining elements, etc.) with the source mechanisms of mining-induced earthquakes to understand better the main drivers of seismicity within the Merensky Reef. The energy ratio (Es/Ep) was used as a discriminator to define two classes of seismic events. Shear (Es/Ep >10, 22 events), located between 1226 and 1470 m depths and non-shear (Es/Ep <10, 51 events), concentrated from 907 to 1460 m below and above the Merensky Reef. About 76% of these seismic events were related to elements of the mining geometry (pillars, abutments, and back-areas); while 24% were located near known geological structures (faults, dykes). INTRODUCTION As the depth of underground mining increases, the stresses in the rock mass increase, and as a result, the level of induced seismicity usually increases. Mine seismicity is a risk to mine personnel and infrastructure. It has become a major operational issue and a problematic planning factor for most underground mines worldwide, particularly at depths greater than 1000 m. As a result, the characterization of rockbursts in the Merensky Reef is critical to understanding the true nature of seismicity and developing mitigation strategies. Given the mine's increased seismicity and risks to production, infrastructure, and mine personnel safety, it is critical to comprehend the rock masses’ behaviour.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".