Large-scale destress blasting for seismicity control in hard rock mines: A case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Destress blasting is a rockburst control technique where highly stressed rock is blasted to reduce the local stress and stiffness of the rock, thereby reducing its burst proneness. The technique is commonly practiced in deep hard rock mines in burst prone developments, as well as in sill or crown pillars which become burst-prone as the orebody is extracted. Large-scale destressing is a variant of destress blasting where panels are created parallel to the orebody strike with a longhole, fanning blast pattern from cross cut drifts situated in the host rock. The aim of panel destressing is to reduce the stress concentration in the ore blocks or pillars to be mined. This paper focuses on the large-scale destress blasting program conducted at Vale’s Copper Cliff Mine (CCM) in Ontario, Canada. The merits of panel destressing are examined through field measurements of mining induced stress changes in the pillar. The destressing mechanism is simulated with a rock fragmentation factor (α) and stress reduction/dissipation factor (β). A 3D model is built and validated with measured induced stress changes. It is shown that the best correlation between the numerical model and field measurements is obtained when the combination of α and β indicates that the blast causes high fragmentation (α = 0.05) and high stress release (β = 0.95) in the destress panel. It is demonstrated that the burst proneness of the ore blocks in the panel stress shadow is reduced in terms of the brittle shear ratio (BSR) and the burst potential index (BPI).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it