Unified closure relationship for slug liquid holdup
Bibliographic record
Abstract
Abstract Slug flow is a common flow pattern in pipes operating with gas–liquid mixtures. The slug flow's periodic behaviour affects the performance of multiphase transportation systems, which is generally predicted using mechanistic models. Mechanistic models are based on one‐dimensional mass and momentum conservation equations and require additional relationships to define a complete system of equations. These additional equations are usually called closure relationships. The slug liquid holdup () is one of the required closure relationships. In this paper a unified closure model for is proposed considering the energy balance and the interaction between inertial, gravitational, viscous, and surface tension forces. The model parameters' behaviour is described as a function of a new dimensionless number. The experimental data analysis shows that this number can quantitatively define two flow categories: ‘low viscosity flow’ and ‘medium/high viscosity flow’. Slug liquid holdup changes its behaviour in these regions due to the predominance of inertial–surface tension forces or gravitational–viscous forces, respectively. The proposed closure performs better than the existing mechanistic and empirical models.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".