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Record W4413795411 · doi:10.26583/sv.17.3.06

Shadow Visualization of Water Droplets Breakup Process in a Laval Nozzle Two-Phase Flow

2025· article· en· W4413795411 on OpenAlexaboutno aff
S. S. Popovich, A.G. Zditovets, Urii A. Vinogradov

Bibliographic record

VenueScientific Visualization · 2025
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsnot available
FundersLomonosov Moscow State University
KeywordsBreakupNozzleFlow visualizationMechanicsVisualizationShadow (psychology)Two-phase flowFlow (mathematics)Process (computing)Phase (matter)Materials scienceComputer graphics (images)Computer scienceMechanical engineeringPhysicsEngineeringPsychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.317
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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