Two-Zone Model for Predicting the Trajectory of Liquid Jet in Gaseous Crossflow
Bibliographic record
Abstract
A hybrid Eulerian–Lagrangian approach was used to develop a model for predicting the penetration of a liquid jet in a subsonic gaseous crossflow. This was achieved by taking into account the effect of all forces acting on the jet, including drag, gravitation, and surface tension, as well as the mass shedding from the liquid column. The effect of mass shedding from the liquid column and jet Reynolds number on the spray penetration height was also studied. It was found that, although the momentum flux ratio plays a predominant role in the prediction of a liquid jet column, the liquid jet penetration can be affected when changing the ambient temperature and pressure (or gas to liquid density and viscosity ratio), especially when holding constant and jet velocity . Two correlations were developed in the form of sinusoidal-exponential and logarithmic function for the prediction of liquid column and droplets’ plume regions, respectively. The proposed correlations are capable of predicting jet penetration of different liquids in a subsonic crossflow at different operating conditions and injection angles. The predictions showed reasonable agreement with published experimental data and empirical correlations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".