Effect of GCL Properties on Shrinkage When Subjected to Wet-Dry Cycles
Bibliographic record
Abstract
The potential shrinkage of eight different geosynthetic clay liners (GCLs) subjected to wetting and drying cycles is examined. It is shown that the initial (e.g, off-the-roll) moisture content may affect the initial shrinkage but did not notably affect the final equilibrium shrinkage. For GCLs with granular bentonite and wetted to a moisture content of about 60% (or greater) in the hydration phase, the actual moisture content did not appear to affect the magnitude of the final equilibrium shrinkage. However, it did affect the rate of shrinkage. Specimens brought to about 100% moisture content in each cycle reached a constant shrinkage value much faster than those brought to about 60% in each wetting cycle. GCLs containing powdered bentonite generally shrank more than those containing granular bentonite. All of the powdered bentonite specimens continued a slow accumulation of strain with increasing cycles, even up to 75 cycles. The shrinkage of a needle-punched GCL with a thermally treated scrim-reinforced nonwoven carrier geotextile and granular bentonite was less than that for a needle-punched GCL with a simple nonwoven carrier and granular bentonite. For some products, there was considerable variability in GCL shrinkage for specimens from the same roll and tested under nominally identical conditions, whereas for other products, the variability was relatively small. The shrinkage strain required to cause the loss of a 150–300 mm panel overlap is shown to be able to be mobilized in about five wet-dry cycles in the experiments reported.
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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 | 0.000 | 0.000 |
| 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".