A Numerical Study of Entrainment Mechanism in Axisymmetric Annular Gas-Liquid Flow
Bibliographic record
Abstract
The main purpose of this study is to investigate liquid entrainment mechanisms of annular flow by computational fluid dynamics (CFD) techniques. In the modeling, a transient renormalization group (RNG) k-ε model in conjunction with an enhanced wall treatment method was employed. In order to reconstruct the two-phase interface, the volume of fluid (VOF) geometric reconstruction scheme was adopted. Simulation results indicated that disturbance waves were generated first on the two-phase interface and that their evolution eventually resulted in the liquid entrainment phenomena. The most significant accomplishment of this work is that details of the entrainment mechanism are well described by the numerical simulation work. In addition, two new entrainment phenomena were presented. One entrainment phenomenon demonstrated that the evolution of individual waves caused the onset of liquid entrainment; the other one showed that the “coalescence” of two adjacent waves (during the course of their evolution) played an important role in the progression of liquid entrainment. Further analysis indicated that the two entrainment phenomena are inherently the same entrainment mechanism. The newly developed entrainment mechanism is based on conservation laws.
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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 | 0.001 | 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".