Effects of bed slope on the flow field of vertical slot fishways
Bibliographic record
Abstract
Abstract Vertical slot fishways (VSFs) are the most efficient and least selective typology of technical fish passage, due to their ability to remain effective even when significant upstream and/or downstream water level fluctuations occur. Fishway construction costs can be reduced by increasing its bed slope, but this affects the flow field inside the pools, with higher head drops between the basins, as well as turbulence levels and flow velocities, which may affect fish passage. In light of this, a VSF was investigated by 3D numerical simulations to identify the possible effects of the bed slope (using values from 1.67% to 10%) on the flow field and subsequent implications for fish passage. A particular focus was devoted to cyprinind species, but the results can be extended to other species of similar swimming abilities and, therefore, be applicable to multispecies rivers. Flow velocity and turbulence values such as turbulent kinetic energy and Reynolds stresses were analysed from a fish passage perspective in relation to threshold values derived from previous studies. Pool areas where turbulence values are compatible with fish ability and behaviour were quantified. Maps of the location of fish‐friendly zones in the VSF pools were produced and can constitute a reference for practical applications in fishway design. The flow field generated with bed slopes lower than 6.67% is more compatible with fish swimming capabilities, because it exhibits a predominantly 2D behaviour and more suitable hydraulic conditions, whereas at higher slopes, turbulence levels in the pools increase.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".