SAFETY ASSESSMENT FRAMEWORK FOR EVALUATING STABILITY IN STANDING IN THE FLOW BELOW A WEIR OR LOW HEAD DAM
Bibliographic record
Abstract
Three hundred two fatalities have been reported at dams in Canada among three hundred sixty-seven safety incidents, and approximately thirty-one percent of the incidents have been at low head dams or weirs. Many of these fatalities occurred due to the misjudging of flow conditions below the weir or dam. Overflow structures such as low head dams and weirs often result in the formation of submerged hydraulic jumps immediately downstream. People who are kayaking, swimming, and fishing around the sites often consider submerged hydraulic jumps as safe because the water surface looks reasonably calm. However, the submerged hydraulic jump has a large roller that produces a countercurrent surface velocity. If a person falls into the flow below the weir, this strong backward flow in the roller can be life-threatening. For this reason, the submerged hydraulic jump is known as a “drowning machine.” However, it is not only the presence of a roller that makes the flow dangerous; it is the magnitude of the forces acting on a human body and the flow velocities due to the presence of the roller that might make it impossible for a person to stand in the flow. In this study, a force-based framework was developed to evaluate the stability of a person who is trying to stand within the recirculating flow of a submerged hydraulic jump. The framework was then applied to assess the flows for which it would be impossible to stand below the structure at the Wolf River Sea Lamprey Barrier on the Wolf River in Ontario, Canada. At this barrier, submerged hydraulic jump conditions exist over a large range of flows. The framework is used to assess the stability of a person based on the net moment generated by forces about two points of balance. To calculate the net moment, methodologies for calculating forces such as the person’s weight, buoyancy, and drag and respective moment arms for those forces were developed. For this work, dimensionless relationships were generated for variation of the frontal area and submerged volume of a person with flow depth, which is necessary for calculating the drag forces and buoyancy. For these work, two-dimensional and three-dimensional male and female body models were created. The change of the center of buoyancy with flow depth was also estimated to find the moment due to buoyancy for a particular flow depth. A method of predicting the velocity profiles below the weir as a part of the drag force calculations on the bodies was also developed. Velocity profiles predicted for the flow below the Wolf River Barrier were compared to the velocity profiles measured in experiments in a scale model of the barrier by Mazurek et al. (2008). The proposed method for predicting velocity profiles showed good agreement with the experimental data. The framework was then applied to assess the maximum safe discharges for standing below the Wolf River Barrier. By analyzing velocity profiles at different downstream locations for six flow rates, it was concluded that the maximum safe discharge is between 15 and 17 m3/s.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".