Study of kerosene–water two‐phase flow characteristics in vertical and inclined pipes
Bibliographic record
Abstract
The kerosene–water flow in vertical and inclined pipes of 77.8 mm inner diameter and 4500 mm length has been investigated numerically. Simulations were carried out at three inclination angles of 0°, 5° and 30° from vertical for superficial water velocities in the range of 0.29–1.6 m/s and volumetric qualities in the range of 9.2–65.5%. Results from the simulations have been compared with the corresponding experimental data from our previous study to check the suitability of meshing, physical models and boundary conditions used. The results from CFD predictions show a reasonable agreement with the experimental data for the vertical pipe. Some discrepancies have been observed near the walls for inclined pipes as the flow becomes more complex with the appearance of drops swarms. The same computational domain was then used to investigate the effect of a higher volumetric quality and superficial water velocity on the flow characteristics. The axisymmetrical distribution of the volume fraction, water velocity and drops velocity which were observed in the vertical pipe has changed into asymmetrical distribution in the inclined pipe. It has also been observed that increasing the superficial water velocity and volumetric quality modifies the distributions of flow parameters due to the movement of kerosene drops toward the lower part of the pipe. The results from CFD predictions on the volume fraction distribution at 30° inclination indicate the appearance of phase inversion phenomenon when the volumetric quality becomes greater than 65%.
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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 | 0.000 |
| 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".