PDPA Investigation on an Electrostatically-Assisted Twin-Fluid Atomization Flow
Bibliographic record
Abstract
The Phase Doppler Particle Analyzer (PDPA) technique is utilized for characterizing the droplet sizes and velocity profiles in an electrostatic spray flow which is atomized using the aerodynamic forces assisted with electrostatic forces. An electrostatically-assisted twin-fluid atomization system is presented and spatial distributions of the droplet size and two-dimensional velocity components are measured simultaneously at each specified point. The droplets are firstly ejected from a liquid jet through the nozzle by aerodynamic shear forces, and the breakup mechanism of such an electrostatically-assisted twin-fluid atomization is investigated using the Rayleigh instability conditions through studying the specific surface charges on these droplets measured by a Faraday canister. The discrepancies between experiment data and Rayleigh limit for specific charges of droplets are presented and discussed due to energy transforming from electrical energy to surface energy, energy loss, Taylor instability breakup and nonexcess charge polarization. The measured average velocity profiles and their RMS (root mean square) velocity values for two different scale drops further reveal the effects of the aerodynamic and electrostatic forces on the atomization process.
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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 | 0.001 |
| 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) | 0.001 | 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".