Towards mining schedule optimisation constrained by geomechanics
Bibliographic record
Abstract
This paper reports work-in-progress that has the aim of incorporating geotechnical constraints on the optimisation of schedules of underground mine excavation activities. Optimal mine schedules are those for which the net present value (NPV) is maximised under a given financial model. The approach aims to consider the visco-elastic behaviour of rock when analysing the stability of excavations for constraint formulation. Changes in deviatoric stress around multiple, sequential openings or excavations are mapped and are shown to be influenced by both changes in the time between excavation events and the sequence of excavating events. The results of this analysis are presented in this paper. The approach is predicated on a causality principle for mine seismicity which requires a time dependent response (visco-elastic or possibly visco-elasto-plastic) of the rock mass. This is potentially difficult to conceive for rock masses at great depth, but is nevertheless evidenced by mine seismicity records from deep level mining operations, some of which are reviewed in this paper. The output of these geotechnical sequencing studies will ultimately be cast as constraints on a mine schedule optimisation process.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".