Correlations of the Droplet Size-Velocity of the Two-Phase, Air/Liquid Spray Using a Particle-Dynamic-Analyzer
Bibliographic record
Abstract
In the heavy oil process industry preheated bitumen and steam are mixed upstream of the feed nozzle and subsequently injected into fluid bed coker reactors via feed nozzles. To achieve high liquid product yields, the bitumen should contact a large number of fluidized coke particles quickly and uniformly. One of the drawbacks of the spray issuing from the nozzle is the potential pulsation within the spray and in the feeding conduit, which is highly undesirable to yield high productivity. These pulsations result in poor atomization and in most instances, a slug of liquid is ejected out of the nozzle. It would be valuable to investigate under which two-phase fluid conditions this pulsation aggravates. It would also be beneficial to examine the detailed spray map with changing air-to-liquid ratio (ALR) by mass and void fraction (α). The average void fraction in the feeding conduit was measured by a pneumatic controlled quick-closing-valve (QCV). The length and diameter of the feeding conduit was 36.8 cm and 6.35 mm, respectively. 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 (ALR) mass ratios of 0.30 to 9.3%. This study indicates that there exists a strong positive correlation between the droplet diameter and axial velocity at the center of the spray. A positive correlation also exists in between the spray center and periphery. However, a strong negative correlation exists at the periphery of the spray. Knowledge from this study would help the heavy oil process industry to upgrade their heavy oil upgrading process and increase the product yield.
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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 | 0.001 | 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".