Time and temperature effects on geomembrane strain from a gravel particle subjected to sustained vertical force
Bibliographic record
Abstract
Experimental data is reported that quantifies how time (up to 10 000 h) and temperature (from 22 to 85 °C) impact tensile strains in a 1.5 mm thick high-density polyethylene geomembrane — with a compressible clay liner beneath it — that are induced by an overlying gravel particle when subjected to a sustained vertical force. At an average applied stress of 250 kPa and clay water content of 16%, tensile strains were found to increase by 1.25 times as the temperature was increased from 22 to 55 °C after 1000 h. Similarly, strains were found to increase by factors between 1.2 to 1.3 as time was increased from 10 to 1000 h. Based on the measured data, time–temperature superposition (tTS) was then used to develop an approach to predict long-term geomembrane strains from gravel indentations. The tTS approach was validated against independent experiments conducted for 10 000 h (1.14 years) as it was found that the predicted strain of 19% was very close to the measured strain of 18%. Provided that the physical properties of the geomembrane do not decrease abruptly, the results suggest that the tTS approach developed can be used to provide estimates of long-term geomembrane strains.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".