Innovative designs for extreme mining applications using bituminous geomembranes
Bibliographic record
Abstract
The paper describes how bituminous geomembranes (BGMs) are designed in innovative ways to solve engineering challenges on mining sites in extreme environmental conditions and to provide environmental protection. The design of BGMs in mine tailings facilities and environmentally sensitive mine waste capping are focused on, and the technical challenges facing these projects are discussed in detail. The protection of groundwater by using effective and puncture resistant BGM solutions contribute to creating a resilient planet. The innovative use of special high friction angle BGMs on the very steep (1V:1.75H) tailings storage embankments of the new large Ravenswood Gold Mine in Australia are discussed in detail. This mine is under construction from 2021 to 2023. BGMs are multi-layered composite geomembranes with each of the components providing a technical benefit on the mining site. These technical advantages include: Extreme puncture resistance, which allows rapid deployment on rougher subgrades; Excellent resistance to wind uplift due to their high surface mass and this means that installation can continue in winds up to 40km/h. Elastomeric BGMs also retain their flexibility in extremely cold conditions and can be installed and welded down to −25 deg C. This means that elastomeric BGMs are often used in the extreme mining conditions of Siberia, northern Canada and the high altitudes of the Andes mountains in South America. BGMs have a very low coefficient of thermal expansion and do not wrinkle with changes in temperature like other polymeric membranes do and this is particularly useful in high heat projects in Australia. This provides a more secure project in the long run, with less risk of wrinkle-induced cracks and failures. In summary, the paper describes how the technical attributes of the BGM&s;s composite structure provides a wide range of practical on-site solutions for challenging mining applications and environmental protection.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".