Long-term Field Performance of Geomembrane-Lined Cover Systems at Mine Waste Rock Piles
Bibliographic record
Abstract
Mine waste rock piles (WRPs) are anthropogenically created landforms at active and former mining sites that can generate and release highly toxic acid mine drainage (AMD) to the environment. A common solution to control AMD generation is the use of cover systems at the WRPs to isolate the reactive waste from water and oxygen in the atmosphere. Geomembranes exhibit the characteristics needed to be highly effective barriers to atmospheric influx; however, knowledge on their performance at in-service WRPs is limited. The objective of this thesis is to comprehensively assess the field performance of geomembrane-lined cover systems for limiting meteoric water to the waste rock. Four coal mine WRPs located in the Sydney Coalfield in Nova Scotia, Canada, were reclaimed with different cover systems and then extensively monitored for seven years. Defect leakage and water balances methods were employed to determine the daily water flux through the cover systems at each WRP over seven years. Results demonstrated that the inclusion of geomembrane liners in cover systems reduced the water influx from 28% of precipitation to as low as 0.05%. Furthermore, the composition of the drainage layer overlying the geomembrane influences the water influx, with native soil, granular material and geocomposite nets providing influx rates of 3%, 0.5% and 0.05%, respectively. This thesis highlights the role of geomembrane liners and drainage layers in engineered cover systems for significantly limiting the influx of meteoric water to mine waste rock.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".