A discrete element modelling of gravity flow in sublevel caving considering the shape and size distribution of particles
Bibliographic record
Abstract
One of the most significant challenges for cave mining methods is dilution, a process which is generally controlled by the gravity flow of caved materials. In this study, the discrete element method (DEM) was used to investigate the effects of changing the porosity of blasted ring material and caved waste rocks and of changing the ring inclination on material flow in a sublevel cave (SLC) mine. Yade software was used to simulate two-dimensional gravity flow in a longitudinal section of the sublevel while taking into consideration the shape and size distribution of the flowing rock particles. Four simulations were generated with different porosities, and the material flow in the models was compared to each other. The results demonstrate that when ring porosity is increased, dilution decreases, and the height of the extraction zone grows longitudinally. Also, a lower porosity of the blasted ore material in the ring can cause early dilution entry and expansion of the extraction zone towards the caved waste.. Finally, the effect of ring inclination on the material flow and dilution was investigated. The results of these simulations show an increased dilution as the ring inclination increases and a change in the shape of the extraction zone.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".