Correlations between the two-phase gas/liquid spray atomization and the Stokes/aerodynamic Weber numbers
Bibliographic record
Abstract
The The effects of air-to-liquid ratio (β) and void fraction (α) on Sauter mean diameter (SMD or D32), arithmetic mean diameter (D10), surface mean diameter (D20), volume mean diameter (VMD or D20), and radial velocity profiles were experimentally investigated for a two-phase gas/liquid (TPGL) nozzle with a hybrid design of classical twin-fluid and effervescent nozzles. Radial spray profiles were measured using a Phase-Doppler-Particle-Anemometer (PDPA) system on 15Dn, 30Dn, 60Dn, 120Dn;(Dn represents nozzle diameter = 3.10,mm) axial distances. In addition, the effects of spray break-up patterns were analyzed with changing axial distances. The average void fraction in the feeding conduit (FC) was measured by a pneumatic controlled quick-closing-valve (QCV). The experiments were performed using mixtures of air with water at water flow rates of 1.50 to 7.50 kg/min and air-to-liquid mass ratios (β) of 0.30 to 10;%. The length and diameter of the FC was 36.8,cm and 6.35,mm, respectively. Result indicates that as the St number reaches the value of one, no more break-up continues, thus the droplets start to coalesce each other forming bigger droplets (higher D10 values) with increasing radial distances. Knowledge from this study will provide better understanding that ensures an increase in plant efficiency and product yield in oil sands bitumen upgrading.
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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 | 0.002 |
| 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".