Estimating Probability of Instability of Haulage Drift with Respect to Mining Sequences
Bibliographic record
Abstract
Haulage drifts play a vital role in providing personnel and equipment access to ore extraction areas for mine production.Thus, their stability is of crucial importance during the life of a mine plan.Many Canadian mines use longhole mining methods or one of its variants.These methods require access to the orebody through haulage drifts on multiple levels.This paper examines the stability of mine haulage drifts with respect to planned mining sequence.A case study of an underground mine is presented.The case study examines #1 Shear East of the Garson Mine in Sudbury, Ontario.A two-dimensional, elastoplastic, finite difference model (FLAC 2D) is developed for a haulage drift situated 1.5 km below surface in the footwall of the orebody.The stability of the haulage drift is evaluated in terms of the spread of yield zones into the rockmass due to nearby mining activities.The performance of the drift stability is evaluated at various mining stages, employing the RMC (Random Monte-Carlo) technique in conjunction with finite difference modeling to study the probability of unsatisfactory performance of the drift.The results are presented and categorized with respect to probability, instability and mining stage.
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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".