Air–water interactions during rapid filling of a closed horizontal pipe
Bibliographic record
Abstract
Rapid filling processes in urban water infrastructure, involving open-channel to pressurized flow transitions with complex air–water interactions, require precise understanding of transient pressure surges, air entrapment and air discharge mechanisms. This study establishes the first experimental framework classifying rapid pipe filling into four distinct stages: advancing bore (stage I), reflection bore (stage II), air intrusion bore (stage III), and residual air release with subsequent inertial oscillations (stage IV). Quantified parameters including bore speeds, pressure and air discharge rate evolutions during each stage, are systematically correlated with gate opening and inlet head, establishing novel predictive relationships. The arrival of the reflection and pipe-filling bores at the shaft can induce significant pressure surges, with peak magnitudes reaching 2.3 times the inlet head through newly identified scaling law dependent on operational parameters. The advancing, reflection and air intrusion bores all cause significant air discharge through the shaft, and an expression for the maximum air discharge rate is obtained. Critically, over 90% of the initial air is expelled during stages I–III, with 28%–77% expelled in stage I, which accounts for less than 11% of the total filling duration. The air discharge volume in stage I increases as the gate opening and inlet head increase. These findings provide a critical foundation for the development of validated transient air–water flow models, predictive mitigation of pressure surge risks, and optimization of resilient urban water infrastructure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".