Field Evaluation of Discretized Model Setups for the Storm Water Management Model
Bibliographic record
Abstract
The Stormwater Management Model (SWMM) is a hydrologic-hydraulic model often used to simulate water flows in urban drainage systems and changes in water quality. The unsteady flow hydraulic solver in SWMM solves mass and momentum conservation equations for the entire conduit length, and mass is conserved at each junction. This link-node approach used by SWMM does not allow for discretization (i.e. intermediate calculation points) between consecutive junctions, which is adequate in gradual filling scenarios with appropriate calibration and suitable selection of routing time steps. However, because there are more rapid filling scenarios that are associated with intense rain events, the link-node solution approach will affect the accuracy of the hydraulic calculations. This work presents the results of a field investigation in which predetermined volumes of water were suddenly released into a physical stormwater collection system. Level loggers were installed to measure flow depth and outflow rates in these tests.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| 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".