Short-Term Local Tensile Strains in HDPE Heap Leach Geomembranes from Coarse Overliner Materials
Bibliographic record
Abstract
Local tensile strains in a 1.5-mm-thick high-density polyethylene (HDPE) geomembrane induced from coarse overliner soil materials intended to simulate the physical conditions at the base of a heap leach mineral extraction pad under very deep burial are reported. They were obtained from physical experiments conducted in a 590-mm-diameter pressure vessel at applied vertical pressures up to 3,000 kPa for 100 h and a temperature of 21°C. An applied pressure of 3,000 kPa corresponds to a heap leach depth of around 150 m. Three different coarse-grained overliner materials placed directly above the geomembrane and a silty sand underliner beneath the geomembrane were examined. Both the grain size and grain size distribution of the overliner affected the maximum tensile strain in the geomembrane. At an applied pressure of 3,000 kPa, the largest strain of 27% recorded for the coarsest overliner tested, which had a maximum particle size of 50 mm and 20% sand, well exceeded one proposed maximum allowable strain limit of 6%. Finer overliners with both a smaller maximum particle size (25 mm) and much more sand (35 and 55%) reduced the geomembrane strains, but the maximum values still exceeded 6% by a factor of 2, even for the finest overliner examined. At these high pressures, a 150-mm-thick silty sand protection layer between the geomembrane and even the coarsest overliner examined was found to be very effective at reducing local indentations in the geomembrane from overliner particles and was able to reduce the tensile strain in the geomembrane to 2%.
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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 | 0.000 |
| 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".