Full-scale experimental testing of dump-point safety berms in surface mining
Bibliographic record
Abstract
Waste rock (muck) piles are used as energy absorption barriers in many surface mining applications, such as berms at dumping points and at the crest of slopes, and in windrows as traffic separators or edge barriers on haul roads. The height of safety berms and windrows is currently designed using rules of thumb, such as height equal to half the maximum wheel diameter. However, over the last few decades, the dimensions of haul trucks have increased, and it is unclear if such rules of thumb are still applicable. This study, funded by the Australian Coal Association Research Program (ACARP), was carried out with the objective of improving the current knowledge on design and construction of dump-point safety berms in mining environments. Through full-scale experimental investigations on the dynamic impact of haul trucks on dump-point safety berms, significant data on berm design, construction materials, as well as principal berm characteristics were collected for the first time. The experimental findings suggested that the current rule of thumb might only be suitable for dump points where trucks travel at velocities lower than 10 km/h. The studies also showed that safety berms should be built using fresh, blocky, nonslaking waste rock materials and well maintained over their lifespan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".