Observation Well Backfilling with Low Strength Grout at the WAC Bennett Dam, Canada
Bibliographic record
Abstract
Telescoping inclinometer casings referred to as observation wells (OW) located within the core of the WAC Bennett Dam were backfilled with specially designed grout using a carefully devised grouting method to ensure the safety of the dam and that no voids were left in place. During initial dam construction, a series of 76.2 mm inner diameter OWs up to approximately 174 m deep were installed within the dam core to monitor lateral displacements and settlement of the embankment. Each OW is comprised of interlocking aluminum half shells joined with external couplings. Seepage flows measured downhole indicated leakage through the casing joints. To avoid ongoing pressure imbalances which lead to sudden drops in water level, a remedial backfilling program was planned and executed. Dam instrumentation was also installed during the backfill grouting to allow continued monitoring of the surrounding embankment. This additional instrumentation limited the available downhole space and necessitated the development of specialized tremie placement methods and equipment to safely complete the work without damage to the dam. Prior to sealing the casings, a series of bentonite-rich, cementitious grouts were tested and evaluated using full scale mixing equipment. The intent of the mix testing program was to develop a grout mix with rheological properties suitable for completing the backfilling of the observation wells, and with physical properties similar to the dam core. These included targets for grout viscosity, shrinkage, compressive strength, strain, hydraulic conductivity, resistance to washout and erosion amongst others. Additional consideration was given to grout compatibility with both the mix water to be used on site, as well as the downhole water chemistry and any notable bacteria or sediment build-up in the casings. Following completion of the mix testing program and selection of the final mix design, grout placement was successfully carried out on site. This paper summarizes the grout mix testing program and presents a case history describing the field implementation program.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".