Liquid jet primary breakup in a turbulent cross-airflow at low Weber number
Bibliographic record
Abstract
The influence of turbulence characteristics of a cross-airflow including its velocity fluctuations and integral length and time scales on the primary breakup regime, trajectory and breakup height and time of a transversely injected liquid jet was investigated experimentally. Turbulence intensity of the incoming airflow was varied from $u_{rms}/u_{g}=1.5\,\%$ to 5.5 % (where $u_{g}$ is cross-airflow streamwise mean velocity and $u_{rms}$ is the r.m.s. of the corresponding cross-airflow streamwise mean velocity fluctuation) by placing at the inlet of the test section a perforated plate/grid with a solidity ratio of $S=50\,\%$ . Over the range of gas Weber number, $3.1<We_{g}<7.14$ , the ensuing liquid jet exhibited more fluctuations and late breakup transitional behaviour under turbulent airflow conditions than in a uniform cross-airflow. Proper orthogonal decomposition of the liquid jet dynamics revealed that the use of grid caused a rise in the wavelength of travelling waves along the liquid jet, which hindered the transition of the liquid jet primary breakup regime from enhanced capillary breakup to the bag breakup mode. The quantitative results demonstrated that, at a constant airflow mean velocity, turbulent cross-airflow caused the liquid jet to bend earlier compared with its uniform counterpart. A power-law empirical correlation was proposed for the prediction of the liquid jet trajectory which takes into account the effect of turbulent Reynolds number. The liquid jet breakup height (in the $y$ -axis direction) normalized by the jet diameter, and accordingly the liquid jet breakup time normalized by the airflow integral time scale, were found to decrease with increasing the airflow turbulence intensity. Two power-law empirical correlations were proposed to predict the liquid jet breakup height and time.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".