Mechanisms for Stormwater Surges in Vertical Shafts
Bibliographic record
Abstract
A number of large scale combined sewer systems have experienced events in which surges have resulted in the return of poor quality stormwater to grade in what are referred to as geysers. In spite of current concerns that these events be avoided by the proper design of new systems, there have been limited investigations to understand the conditions that lead to these surges or how to avoid them. In the course of an ongoing investigation into the dynamics of rapidly filling pipelines, two phenomena have been identified that may result in geyser-like phenomena. Both of these are associated with the movement of a large pocket of entrapped air along the crown of a nearly horizontal pipe. One case occurs when the leading edge of the air cavity arrives at a vertical riser at a location along the pipeline that is already in a surcharged state. A second case occurs as the trailing edge of the same air pocket arrives at the riser and the pipe is not in a surcharged condition. Experiments have been performed to reproduce both of these situations in a simplified fashion where several of the key variables can be controlled. The features of these experiments are described as well as some of the results obtained to date. These results are interpreted to identify aspects of a storage tunnel system that are under design control and how these affect the magnitude of the observed surges. Finally, since the experiments are performed in a relatively small-scale apparatus, speculation is presented on
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".