Long-term performance of polyethylene geomembranes to contain brine
Bibliographic record
Abstract
The degradation of five fortified polyethylene geomembranes (three HDPE, one LLDPE, and one blended) with high initial properties compared to minimum requirements in GRI-GM13 is investigated when immersed in brine at three concentrations (100%, 50%, and 10% brine) and deionized water at temperatures ranging from 25 to 95°C for 8 years. The performance of the geomembranes in different incubation fluids is compared to explore the effect of salt concentration on the durability of geomembranes. The results indicate that the high initial properties of a GMB may not be indicative of its long-term performance due to the effect of other factors like GMB resin, stabilizers, thickness, exposure conditions, and manufacturing process on GMB degradation. Increasing salt concentration decreases the rate of antioxidant depletion, with a depletion rate in 10% brine 1.5 times faster than that in 100% brine. Thus, any assessment of the likely service life of a polyethylene geomembrane in a brine pond with variable salt concentration requires investigating their performance over the expected range of brine concentrations. Temperature and choice of geomembrane (especially antioxidant package) are shown to have a significant (e.g., by a factor of 4 at 55°C in brine) effect on liner longevity. • Examines how high initial OIT and SCR properties affect the longevity of polyethylene geomembranes in brine. • Investigates salt concentration's impact on the degradation of five polyethylene geomembranes in brine impoundments. • Compares the degradation behaviour of the five polyethylene geomembranes in brine with their degradation in deionized water.
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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 | 0.001 |
| 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".