An approach to high-density polyethylene (HDPE) geomembrane selection for challenging design requirements
Bibliographic record
Abstract
An approach for selecting a high-density polyethylene (HDPE) geomembrane (GMB) for a long design life is described and illustrated for five 2 mm thick textured GMBs when immersed in a simulated municipal solid waste leachate (L3) and two simulated leachates representative of low-level radioactive waste leachates (L7 and L9) for 9–16 months at a range of temperatures. Although made from the same nominal resin, substantial differences are reported in both the initial properties and the rate of antioxidant depletion for the five GMBs. At an expected operating liner temperature of 10 °C and immersed in L3, the projected time to antioxidant depletion for the five GMBs ranges from 125 to over 2000 years. The antioxidant depletion in leachates L7 and L9 were similar or slower than in leachate L3. There was no evidence of traditional thermal-oxidative degradation reported over the 9–16 months of monitoring; however, there was a significant reduction in stress crack resistance due to physical ageing ranging between 30% and 70% of the initial value. Two GMBs are considered highly likely to have service life well in excess of the required design life of 550 years. It is suggested that the proposed approach could be adopted for selecting GMBs for other projects that require a long design life.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".