Mixed Grouting Methods and Materials for Under-Seepage Mitigation at Barrage des Quinze Dam, Quebec, Canada
Bibliographic record
Abstract
The Barrage des Quinze Dam is a concrete sluice dam consisting of 19 spillway sections, each of which is approximately 7.6 metres wide and 14.5 metres deep. Rehabilitation efforts being performed on the dam include demolition and improvement of the roadway and spillway sections and grouting to mitigate under-seepage. Multiple approaches to grouting were undertaken to mitigate seepage under the existing dam during the rehabilitation work. The initial grouting was completed with basic cement-water grouts followed by grouting with the addition of Celbex, a thixotropic agent. This approach was successful for all but 5 sluice bays of the dam. Final grouting for the final five sluice bays was planned as a multiple phase approach with low mobility and balanced stable grouts using sodium silicate for set control. The substantial high water flows (leakage) beneath the dam between the concrete/rock contact and within fractures in the upper rock formation created a challenging situation to create a cutoff. A grouting solution was developed that involved implementing several different grouting methods and materials including balanced high mobility grouts (HMG); low mobility grouts (LMG); polyurethane grout; and sodium silicate. This final program was completed in winter conditions requiring special equipment and techniques. The project was successfully completed through the winter months in northern Quebec Province using special measures to protect the work space and provide heating for grout materials for proper injection and cure. The work was completed within the required schedule to enable use of the dam gates to manage spring flows.
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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 | 0.002 | 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 | 0.002 | 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".