DROPLET SIZE-VELOCITY CHARACTERISTICS OF SPRAYS GENERATED BY TWO-PHASE FEED NOZZLES
Bibliographic record
Abstract
The present study focuses on the evaluation of the droplet size-velocity characteristics of sprays generated using two-phase flow feed nozzles. Two types of nozzles were used in the study and for convenience these are designated as Nozzle-A and Nozzle-B, respectively. Liquid nitrogen is used to simulate feeds that undergo vaporization upon injection into the processing vessel and air is used as the carrier gas. For each test, the liquid flow rate and the aeration rate are varied and the droplet size-velocity measurements are conducted using a Phase-Doppler Particle Analyzer. The droplet size and velocity measurements are carried out at various axial locations along the spray. At each axial location, measurements are performed at various radial positions. The main variables of interest include the droplet velocity, droplet diameter, droplet count fraction and the droplet size-velocity correlation factor. The results indicate that the two nozzles considered in the present study generate sprays with varying characteristics. The aeration rate has a larger influence on the spray generated by Nozzle-B. The droplet size distributions are found to be sensitive to changes in the aeration rate. The droplet velocity characteristics are different from those reported in earlier studies on single-phase and droplet-laden jets.
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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 | 0.000 | 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".