A Quasi-Two-Phase Flow Model for Calculating Filling in Pipelines
Bibliographic record
Abstract
This paper presents a quasi-two-phase flow model for simulating filling in water pipe systems. The model employs a shock-fitting algorithm for tracing the water column advancement during filling. The method of characteristics (MOC) along with discreet gas cavity model (DCGM) is utilized to capture the possible water column separation and induced water hammer pressures during filling. The state-of-the-art air valve boundary condition is improved to account for the two-phase flow usually established in the pipe on the downstream side of the air valve. The results show that the proposed model can (1) replicate the negative pressure and consequent water column separation; (2) reproduce the secondary transient pressure following the releasing of the air at air valve locations; (3) simulate controlled air release, a strategy usually employed for alleviating the severity of secondary transient events; (4) capture the final steady state flow condition even when the pipe system maintains both open channel and pressurized flow simultaneously; and (5) reproduce air binding and consequent flow reduction in the case that an air valve fails to release the air from the system.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".