Numerical and limit equilibrium stability analyses of cemented mine backfill upon vertical exposure
Bibliographic record
Abstract
In open stope mines, the cemented backfill must maintain self-standing in the primary stope during the extraction of an adjacent secondary stope. A limit equilibrium solution proposed by Mitchell et al. (1982) has been widely used since the 1980s to design the exposed cemented fill. This solution has been the object of several modifications over the years. Recently, the comparison between these solutions and numerical simulations indicated that the former are not fully representative of the exposed fill when its required cohesion is relatively large. In this paper, new numerical results show that the slip surface transitions from planar at low fill cohesion to spoon-shaped at larger cohesion. In the former case, the failure is controlled by shear stresses mobilised along the planar slip surface. This is very similar to the failure mode assumed in existing theoretical models. In the latter case, however, the failure is governed by both shear (near the base) and tensile (near the top) stresses, indicating a different failure mode. Based on these observations, a new analytical solution is proposed to evaluate the stability of side-exposed cemented fill. This solution is validated using complementary simulations and the results indicate that the two different approaches agree well for typical stope geometry and fill properties.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".