Effect of underliner on the strain and puncture response of a bituminous geomembrane in heap leach applications
Bibliographic record
Abstract
Experiments simulating a bituminous geomembrane (BGM)-lined heap leach pad were conducted to quantify the short-term punctures and gravel-induced tensile strains that could become locations of puncture in the long term. Vertical pressures ranging from 500 to 2000 kPa were examined with attention focused on the effect of the underliner soil type (i.e., subgrade) on the punctures and tensile strains induced in a 4.1 mm thick BGM by a given coarse overlying drainage layer. The examined underliners included predominately gravel, gravel-sand-silt mixtures (tills), silty sand, and compacted clay. It was found that gravel in the underliner and its gradation were the primary drivers of puncture and high strains with underliner gravel fractions as low as 30% (by weight) resulting in BGM puncture. It was also found that the 4.1 mm thick BGM developed substantially (10-fold) more punctures than a conventional 1.5 mm thick HDPE GMB under nominally identical test conditions. Using a stronger 4.8 mm thick BGM resulted in better performance; however, it still developed more holes than a 1.5 mm thick HDPE GMB signaling that BGMs can be more susceptible to static gravel puncture (despite being much thicker and heavier than HDPE GMBs). The importance of conducting cylinder performance tests using site-specific materials and anticipated stresses is demonstrated. The findings in this study, which represents the first extensive study into BGM puncture resistance, may have relevance to BGMs used in other bottom liner applications (not just heap leach pads).
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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 | 0.000 | 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) | 0.001 | 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".