Physical Investigation of Discrete Air Pocket Migration and Release in CSO Storage Tunnels
Bibliographic record
Abstract
Various rapid filling scenarios lead to the formation of large discrete air pockets in below ground storage tunnel systems.The release of trapped air pockets through a vertical shaft can potentially cause a geyser event in which untreated wastewater returns to the ground surface.It is important to the design efforts of these expensive systems to estimate the potential for such events and to provide solutions to mitigate the undesirable effects.However, little is known about the behavior of discrete air pockets once they are trapped within tunnel systems.Initial laboratory experiments were performed to qualitatively assess the main contributing variables for the direction and velocity of air pockets as they migrate within nearly horizontal systems.Experimental data is collected for air pocket migration in the direction of water flow.Next, a diameter expansion within the vertical shaft was investigated as a possible design modification to mitigate geyser events.Experimental variables such as the ratio of expansion diameters and the vertical location of the expansion were investigated to optimize the proposed design.The scalability of experimental results was explored by performing tests on a 0.095 m diameter tunnel as well as a 0.203 m diameter tunnel.Qualitative conclusions are presented and discussed from the experimental results.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".