Shear strength of the geomembrane–subgrade interface in heap leaching applications
Bibliographic record
Abstract
A series of large-scale direct shear tests was carried out to examine the effectiveness of smooth, textured and structured surface geomembranes (GMBs) with different soil subgrades for heap leach pad applications. Four different subgrades – namely, sand, two different coarse-grained underliners and a clayey soil representing the layers directly underlying the GMB liner in heap leach pads – were used to examine the shear strength of the GMB–subgrade interfaces at normal stresses between 50 and 1000 kPa. It was found that increasing the normal stresses can change the mechanisms contributing to the shear resistance at the interface. This resulted in a statistically insignificant increase in the interface friction of the GMB–granular soil interfaces when using GMBs with surface roughness relative to the interface friction of the smooth GMB. Furthermore, depending on the type of subgrade, establishing the shear envelopes over a wide range of normal stresses was found to overestimate or underestimate the shear strength at the field stresses even when linear regressions present the best fit for the data.
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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) | 0.000 | 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".