Modeling of Feed Vaporization in Fluid Catalytic Cracking
Bibliographic record
Abstract
Feed vaporization in the fluid catalytic cracking (FCC) process affects the yield of valuable products in risers and downers. Feedstock droplets sprayed into a fluid cracker undergo both homogeneous vaporization in the gas phase and heterogeneous vaporization as they collide with catalyst particles. This paper models both processes. Homogeneous vaporization, with both convection and radiation heat transfer, cannot completely vaporize oil droplets with diameters larger than 10 μm. Spraying droplets into a dilute cloud of catalyst particles forms a “tunnel” of hydrocarbon vapor that minimizes droplet−catalyst contact and vaporization. Alternately, spraying the droplets onto a dense jet of catalyst particles does not provide proper heat transfer and vaporization. Modeling indicated that the best way of ensuring fast vaporization of oil droplets in FCC risers and downers is to spray the droplets onto a jet of catalyst particles with a porosity ranging between 70 and 90%.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".