Assessment of stope sequence alternatives in a diminishing ore pillar
Bibliographic record
Abstract
One of the primary mine planning abilities of numerical models is their assessment of stope sequence alternatives in terms of the redistribution of mining-induced stresses and the amount of rock face displacements in each of them. The models used for these studies are large and complex in nature as they need to replicate the entire orebody within which the stope sequence is being planned, in addition to the surrounding rock mass. In this paper, a case study is conducted at Vale’s Garson Mine for the stope sequence options of mining in Orebody #1 Shear West, which will result in a central diminishing ore pillar before final extraction. A mine-wide numerical model is first constructed in FLAC3D and calibrated based on an in situ stress measurement point on 4900L (1,495 m) such that the values read in the field are correlated to those generated by the model. The historical stope sequence followed at the mine is then replicated between the years 2001 and 2011, which is when mining is planned to commence between the levels of interest in #1 Shear West. Extraction is planned from both the eastern and western sides of the orebody, and the default sequence is considered to alternate between the two in each successive step as they move towards the diminishing ore pillar. Using the brittle shear ratio – the relationship between the differential stress (sigma 1 to sigma 3) and unconfined compressive strength of intact rock – and volumetric analysis, the planned stope sequence is assessed within the diminishing ore pillar. A threshold of 0.7 is considered as indicative of ore at risk based on the literature and Vale guidelines. A second sequence alternative, in which extraction in the east is accelerated thrice, is also considered and compared with the planned one. A new stope sequence planning tool is introduced to visually and quantitatively compare amongst the two sequences. It is shown that by using the planning tool, the volume of unmined ore (of operational and economical interest) and the volume of ore at risk (of ground control interest) can be quantitatively estimated at any given mining step. Finally, variations in rock mass properties based on laboratory results and borehole logs are considered to assess their effect on the volume of ore at risk in the alternative sequence.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".