Uncertainty in 2-D hydraulic modeling: a case study of an experiment in transcritical flowThis article is one of a selection of papers published in this Special Issue on Hydrotechnical Engineering.
Bibliographic record
Abstract
Change in flow regime from subcritical to supercritical flow or opposite can be met during a dam break flow propagation but also during floods in urban areas, particularly near crossroads. Detailed laboratory measurements of flow discharge distribution and flow depths are carried out for transcritical dividing flows in a 90° sharp-edged, rectangular junction formed by horizontal open-channels of equal width. These measurements are used to assess the uncertainty of numerical predictions obtained using a two-dimensional (2-D) depth-averaged model. A sensitivity analysis to four parameters, i.e., space step, friction coefficient, diffusion coefficient, and downstream boundary condition, is carried out. For the water depths in the vicinity of the intersection, uncertainty linked to the calibration of the four aforementioned parameters can be higher than 50% because of the difficulty in representing the location and amplitude of the hydraulic jumps while, for the flow ratio between the downstream branches, uncertainty is limited to 10%.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".