Depletion of Antioxidants from a HDPE Geomembrane in a Composite Liner
Bibliographic record
Abstract
The results of two series of accelerated aging tests are reported. Both series of tests were conducted at temperatures of 85, 70, 55, and 26°C over a period of about 3years. In the simulated liner series, the top of the geomembrane was covered with a geotextile (protection) layer that was exposed to simulated municipal solid waste (MSW) landfill leachate while the bottom of the geomembrane was in contact with a hydrated geosynthetic clay liner. In the immersion series, the geomembrane was immersed in the simulated MSW leachate, and hence, both sides were exposed to leachate. The results from oxidative induction time tests indicate that the antioxidant depletion is about 2.2–4.8 times faster for the leachate immersed geomembrane than for geomembrane in a composite liner. The higher rates are attributed to the higher extraction of antioxidants from two sides of the geomembrane immersed in leachate. The measured antioxidant depletion rates are extrapolated to a range of temperatures (0–60°C) using Arrhenius modeling. At a liner temperature of 35°C, the calculated time for the depletion of antioxidants is about 40years for a geomembrane in a composite liner compared to 10years if it is simply immersed in leachate. These tests suggest that to obtain realistic estimates of geomembrane service life one needs data from tests that simulate the expected field conditions and that prediction based on immersion tests may underestimate the service 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 | 0.000 | 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".