Self-healing of laboratory eroded defects in a GCL on silty sand
Bibliographic record
Abstract
The self-healing of five geosynthetic clay liners (GCLs) with laboratory simulated down-slope erosion defects (quasi-circular holes and linear slits where there is little or no bentonite) upon hydration from Godfrey silty sand subgrade with wfdn = 16% under an overburden stress σv = 20 and 100 kPa is examined. While there was an up to 9.6 mm reduction in hole diameter/slit width, none of the defects fully self-healed. The self-healing of these laboratory eroded specimens with a swell index of 10.2 ± 1.7 ml/2 g after hydration is generally smaller than that of the corresponding virgin GCLs. GCLs with powdered bentonite with an initial SI of 32 ml/2 g generally self-healed better and the intact specimens had a lower hydraulic conductivity than GCLs with granular bentonite with an initial SI of 24–26 ml/2 g. Higher mass per unit area of bentonite and overburden stress led to better self-healing. Ponding of distilled (DI) water above the GCL increased self-healing of GCL slightly more than simulated synthetic landfill leachate (SSL). The post-hydration hydraulic conductivity, k, of GCL specimens with holes/slits is shown to be about 1–3 orders of magnitude higher than that of the intact GCL specimen.
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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".