Durability of Three HDPE Geomembranes Immersed in Different Fluids at 85°C
Bibliographic record
Abstract
The long-term performance of three different high-density polyethylene (HDPE) geomembranes (GMBs) is investigated at 85°C using immersion tests. By comparing the degradation behavior of the three GMBs in different synthetic leachates, it is shown that different chemical constituents in the leachate affected different stages of the degradation, with surfactant having the greatest effect on antioxidant depletion (Stage I) and salts having the greatest effect on the degradation after antioxidant depletion (Stages II and III). The magnitude of the effect of these chemical constituents differed from one GMB to another. Thus, for the purpose of comparing the relative long-term performance of the three GMBs for municipal solid waste (MSW) landfill applications, the GMBs were immersed in a synthetic leachate (Leachate A), which contained the primary constituents (i.e., salts, volatile fatty acids, surfactant, and trace metals under reduced conditions) present in the leachate from a large MSW landfill leachate located in Canada. At 85°C, the longest antioxidant depletion stage was for the GMB with the highest resistance to antioxidant depletion in Leachate A, even though its initial oxidative induction time values were not the highest of the three GMBs. After antioxidant depletion, the greatest resistance to degradation was for the GMB with the highest initial stress crack resistance and the lowest melt flow ratio.
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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 | 0.001 | 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".