Three-dimensional limit equilibrium analysis of open pits
Bibliographic record
Abstract
The analysis of slope stability in the design and ongoing operations of any particular open pit remains a difficult challenge. Slope failures and loss of equipment, mining time, and lives make stability concerns an issue which warrants research efforts. Engineers have relied for decades on software tools to perform analysis of the slopes of open pits in order to estimate the Factor of Safety (FS). Usually open pit geometry is typical three-dimensional (3D) geometry which cannot adequately be simplified into a two-dimensional (2D) plane strain representation. Traditional analysis has been performed using 2D limit equilibrium methods (LEM) since this method continues to be the simplest to apply. This paper examines the application of the 3D LEM to analyse the slopes of an open pit. The 3D LEM has advantages in that it can consider slips at any particular azimuth vector angle (i.e. it can search the whole 3D open pit model and find the critical slip surface, and critical slip vector). The results of 3D LEM are compared with results from 2D LEM analysis. The result is a methodology which is credible and applicable within a reasonable time frame for the analysis of open pits.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".