Experience in locating leaks in geomembrane-lined ponds
Bibliographic record
Abstract
This study presents the results of five years of applying the dipole method in geomembrane-lined ponds to locate leaks arising from either the construction or operational stage. Inspections were conducted on 136 projects designed with single (n=57) or double (n=79) liner and located in the United States (n=108), Mexico (n=5), or Canada (n=23). The ponds were tested either full or at a depth between 0.3m and 0.8m, both sets of results were compared to the available literature. Approximately 210 ha of primary geomembrane-lined ponds were surveyed, uncovering 825 leaks during the study period. An average number of leaks/ha was 13.2 ranging from 0 to 272. The highest results were 272, 242, and 131 leaks/ha in double-lined, and 80 and 77 leaks/ha in single-lined ponds. The inspected data revealed that 43% of projects had 0-2 leaks/ha, 20% had >2-5 leaks/ha, 14% had >5-10 leaks/ha, and 16% of the ponds had >20 leaks/ha. The results of this study are crucial for designers, Landfill Operators, and Environmental Agencies in establishing inspection practiced for lined ponds, particularly after a period of operation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".