Evaluation of StereoPIV Measurement of Droplet Velocity in an Effervescent Spray
Bibliographic record
Abstract
Particle image velocimetry (PIV) is a well known technique for measuring the instantaneous velocity field of flows. However, error may be introduced when measuring the velocity field of sprays using this technique when the spray droplets are used as the seed particles. In this study, the effect of droplet number density, droplet velocity profile, and droplet size distribution of a spray produced by an effervescent atomizer on velocity measurement using a StereoPIV has been investigated. A shadowgraph-particle tracking velocimetry (S-PTV) system provided measurement of droplet size and velocity for comparison. This investigation demonstrated that the StereoPIV under-estimates velocity at near-field dense spray region where measurement accuracy is limited by multi-scattering of the laser sheet. In the dilute far-field region of the spray, StereoPIV measurement is mostly in agreement with velocity of the droplet size-class which is close to the mean diameter based on droplet number frequency times droplet cross sectional area.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".