Effect of nozzle-exit conditions on the near-field characteristics of a transverse liquid jet in a subsonic uniform cross airflow
Bibliographic record
Abstract
Several tapered- and sharp-edge nozzles with different exit diameters were used to investigate their effect on the near-field characteristics of a liquid jet injected transversely into a subsonic uniform cross airflow including a jet’s structure, column trajectory, and its breakup length. The experimental results demonstrated that at a low range of jet velocity, the axial turbulence intensity of a liquid jet issuing from a sharp-edge nozzle is greater than that of a tapered-edge nozzle. This resulted in a more irregular surface of the liquid column injected from a sharp-edge nozzle. However, the presence of hydraulic flip in the case of a sharp-edge nozzle at high jet velocity caused a reduction in the axial turbulence intensity of the injected liquid jet which has a smoother surface. Prior to the occurrence of hydraulic flip, the column trajectory of a liquid jet issuing from a tapered-edge nozzle is similar to that of a sharp-edge nozzle. However, the jet issuing from the latter penetrates farther than the former under hydraulic flip conditions. The presence of hydraulic flip increases the breakup length of a liquid jet. Furthermore, the present experiments allowed estimating the discharge coefficient of each nozzle by comparing with the mathematical correlations developed in our previous studies for predicting the column trajectory and breakup length of a transverse liquid jet. This allowed extending the applicability of these correlations to account for the effect of nozzle’s exit conditions on the near-field characteristics of a transverse liquid jet.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".