Prediction of Geyser Occurrences in Covered Manholes of Urban Stormwater Systems
Bibliographic record
Abstract
Storm geysers are air–water eruptions from stormwater manholes during intense rainfalls, which raise public safety concerns. They arise from entrapped air release in stormwater tunnels as flow transitions from open to pressurized. This paper experimentally investigated air–water flow characteristics during air pocket release in covered manholes. Four geyser regimes were identified: no geyser, single air-release geyser, single rapid-filling geyser, and multigeysers. The air-release geyser and rapid-filling geyser refer to ejections of water column and air–water mixture induced by distinct mechanisms. Impacts of manhole diameter, cover ventilation area, system pressure head, and initial air pocket volume on geyser regimes were analyzed. As manhole diameter increases or cover ventilation area decreases, maximum geyser heights decrease, subsequently decreasing the likelihood of geyser occurrence. Higher system pressure head and larger initial air pocket volume increase the maximum geyser heights. Equations were derived to predict the maximum geyser heights, and prediction accuracies exceeded 87%, providing safe predictions of geyser occurrences relative to the manhole height. The findings can help provide advance warning of geysers when combined with information of stormwater system structures and real-time monitoring of operating conditions.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".