Short- and long-term leakage through composite liners. The 7th Arthur Casagrande Lecture<sup>1</sup>This lecture was presented at the 14th Pan-American Conference on Soil Mechanics and Geotechnical Engineering, Toronto, Ont., October 2011, and a pre-print appeared in the conference proceedings.
Bibliographic record
Abstract
The factors that may affect short-term leakage through composite liners are examined. It is shown that the leakage through composite liners is only a very small fraction of that expected for either a geomembrane (GM) or clay liner (CL) alone. However, the calculated leakage through holes in a GM in direct contact with a clay liner is typically substantially smaller than that actually observed in the field. It is shown that calculated leakage taking account of typical connected wrinkle lengths observed in the field explains the observed field leakage through composite liners. Provided that care is taken to avoid excessive connected wrinkle lengths, the leakage through composite liners is very small compared to a typical GM or CL alone. It is shown that the leakage through composite liners with a geosynthetic clay liner (GCL) is typically much less than for composite liners with a compacted clay liner (CCL). Finally, factors that will affect long-term leakage through composite liners are discussed. It is concluded that composite liners have performed extremely well in field applications for a couple of decades and that recent research both helps understand why they have worked so well and provides new insight into issues that need to be considered to ensure excellent long-term liner performance of composite liners — especially for applications where the liner temperature can exceed about 35 °C.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".