Special repairs to the Bersimis-1 generating tunnel walls to increase power production: a case study
Bibliographic record
Abstract
The intake concrete tunnel at Bersimis-1 generating station is coated with a black sticky substance (slime) approximately 5 mm in thickness. Since the tunnel is 12 km long and has an average internal diameter of 9.45 m, the deposit represents a considerable obstacle to the production of electric power. The resulting loss of power generated is estimated to be around 39 MW per year, valued at 71 million dollars. Inspections in 1979, 1981, and 1983 showed that simply cleaning the surfaces would reduce the power losses but the slime built up again after a few years. A thin, smooth protective coating, containing anti-slime agents, compatible with the existing concrete could protect the surfaces against erosion and limit the slime deposit and its harmful effect on power production. The 1993 inspection provided an opportunity both to analyze the concrete, the slime itself, and the water and to experiment with the various methods of cleaning the surface and applying the different coating products. In 1994, 11 other products were selected for the specified characteristics and applied on concrete pipes and installed at two different locations: one consisted of submerged concrete specimens in the Bersimis river and in the second test setup, the products were installed by creating an artificial environment similar to the tunnel conditions using the tunnel water. The results showed that some products do not resist these conditions. Abrasion resistance tests in the laboratory confirmed these observations. One of the eleven products, a polymer-modified cement-based mortar, passed the submersion test and was applied to a small surface area (125 m2) of the tunnel during a generating station shutdown in 1995. The thickness of the mortar required to cover the walls of the tunnel was between 2 and 3 mm. The total cost of repairing with the mortar was estimated to be between 10 and 11 million dollars. The size of the tunnel, its restricted accessibility, cleaning, ecological disposal of the slime, and the large quantities of material to be applied to cover the entire tunnel added to the complexity of the project.Key words: intake tunnel, power production, protective coating, slime deposit, surface cleaning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".