Shadow Visualization of Water Droplets Breakup Process in a Laval Nozzle Two-Phase Flow
Bibliographic record
Abstract
The results of an experimental study of an air-droplet flow in a flat supersonic Laval nozzle of a periodic-acting wind tunnel are presented. The droplets were fed into the flow using fine spray nozzles installed in the pre-chamber. The working part of the wind tunnel has a rectangular cross-section with dimensions of 70x98 mm. The Mach number at the nozzle exit varied in the range 2,0-3,0 due to the mechanism of compression of the nozzle critical section, the total pressure in the pre–chamber was 450-550 kPa, and the total temperature was 288-298 K. The initial concentration of the dispersed (liquid) phase in the flow and the initial droplet size distribution were varied by changing the pressure drop at the spray nozzles. When studying the dynamics of droplet crushing in the critical section of the nozzle, the SSP (shadow photography) laser method was used, which includes: a flow illumination system based on a Beamtech dual-pulse Nd:YAG laser with a wavelength of 532 nm, a 7-joint optical arm for delivering laser radiation, a light-scattering screen for creating a backlight with alcohol solution of rhodamine phosphor, a digital CCD camera with a frame rate at full resolution up to 15 Hz, an Infinity K2 DistaMax microscope lens and the synchronization processor. A series of snapshots of the instantaneous state of the air-droplet flow in the critical section and in the expanding part of the Laval nozzle were obtained.
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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) | 0.002 | 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".