Physical model testing of sluice operations and riprap scour protection at the West Timiskaming Dam
Bibliographic record
Abstract
The West Timiskaming Dam (Ontario Dam) spans the Ottawa River from the south end of Long Sault Island to the west bank of the river. On the other side of Long Sault Island, slightly further upstream another dam exists (East Dam or Quebec Dam) that spans from the north end of the island to the east bank of the river. The East and West Dams at Timiskaming control the water level in the upstream body of water, known as Lake Timiskaming. The West Dam was completely replaced with a new structure in 2017 and since its completion, the Ottawa River has experienced a large flow event during the spring of 2019. There was concern that scour of the newly placed downstream riprap may have occurred during this large flow event. In order to investigate the hydrodynamic conditions at the West Dam and potential scour of the downstream riprap, a three-dimensional physical model of the West Timiskaming Dam structure, riprap protection, and portions of the upstream and downstream river bathymetry was designed and constructed at a geometric scale of 1:24 in NRC’s research laboratory located in Ottawa, Canada. The model was used to simulate a large number of historic dam conditions including flows, sluice settings and tailwater elevations to investigate the cause of riprap scour downstream of the dam structure. In addition, the model was used to test various options to mitigate future scour potential.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".