Water Leakage Detection Using Optical Fiber at the Peribonka Dam
Bibliographic record
Abstract
A monitoring system based on temperature readings using fiber optic cables was designed for leakage detection through possible defects in the cutoff wall of the Peribonka main dam. The system is based on the heat pulse method to measure the apparent soil thermal resistivity. By combining a line heat source with a fiber optic distributed temperature measurement, local analysis of heat transfer can be performed to detect, locate and estimate the leak percolating velocity. Laboratory tests were carried out in clean granular sand having a hydraulic conductivity (kSat) of 10–3 m/s. The apparent thermal resistivity measured with the system decreased from 0.6 m-K/W to negligible values when the Darcy velocity of the percolating fluid was increased from 10–6 to 10–4 m/s. This shows the capacity of the proposed system for detecting leakage in these kinds of soils. Finite element modeling of the experiments shows the same trend. Three hybrid cables were installed in boreholes through the alluvial foundation of the Peribonka main dam by way of boreholes. The cutoff wall is now completed and preliminary measurements indicate no significant seepage.
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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) | 0.000 | 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".