Design of an open-pit gold mine by optimal pitwall profiles
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Bibliographic record
Abstract
The overall steepness of pitwalls significantly influences the financial return of an open pit mine. In current practice, pitwall profiles are planar in cross-section. In this paper, a new geotechnical software, OptimalSlope, is employed to determine depth-varying optimal pitwall profiles for each slope sector of the mine. OptimalSlope solves a mathematical optimization problem where the overall steepness of the pitwall is maximized for the assigned stratigraphy, rock properties, and Factor of Safety (FoS). Bench geometries (bench height, bench-face inclination, and minimum berm width) are incorporated into the optimization as constraints that bind the maximum local inclination of the sought optimal profile together with any other constraint related to any geological discontinuities that may influence slope failure. The optimal profiles are always steeper than their planar counterparts—that is, the profile exhibiting the same FoS, generally up to 8 degrees, depending on rock type and constraints. To showcase the financial gains that can be achieved via OptimalSlope, the design of a gold mine in a complex geology dominated by weak rocks was initially carried out for planar pitwalls and then for optimal pitwall profiles. The pit has been divided into five geotechnical sectors, each requiring a different pitwall profile design. Adopting optimal slope profiles led to a 52.7% higher net present value and reductions in the carbon footprint and energy consumption of 0.0613 million tonnes CO2 eq and 31.3 million MJ, respectively, due to a 3.5% reduction of rock waste volume.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it