Experimental Study of Superheated Kerosene Jet Fuel Sprays From a Pressure-Swirl Nozzle
Bibliographic record
Abstract
The development of higher thermal stability fuels and the development of onboard fuel deoxygenation systems may permit the preheating of fuel up to about 755 K before the onset of pyrolysis. At a sufficiently high fuel temperature for a given combustion chamber pressure, the flash vaporization of liquid or supercritical state fuel can ensue upon injection into the chamber. The performance of standard aviation turbine engine fuel nozzles, designed for mechanically breaking up liquid sprays, may thus be significantly altered by the employment of severely preheated fuel. An evaluation of heated and superheated Jet A-1 sprays from a pressure-swirl atomizer was implemented in a purpose-built test facility. Laser sheet imaging of the spray yielded simultaneous axial cross-sectional maps of Mie-scatter and fluorescence signals. In addition, particle image velocimetry was also used to measure the spray droplet velocity-field. The results indicated that increasing the fuel’s dimensionless level of superheat ΔT* from −1.8 to 0.6 yielded significant changes in the spray structure; specifically, finer droplet sizes, a more uniform dropsize distribution across the spray, increased spray cone angle till about ΔT* = −0.8 followed by a contraction thereafter, marginally increased spray penetration, and significantly higher localised near nozzle tip droplet velocities. The measurements supported the hypothesis that the initial hollow-cone spray structure evolves to a near solid-cone structure with a central vapour core as the fuel is superheated.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".