Study of Canadian FCC Feeds from Various Origins and Treatments. 2. Some Specific Cracking Characteristics and Comparisons of Product Yields and Qualities between a Riser Reactor and a MAT Unit
Bibliographic record
Abstract
Ten vacuum gas oil feeds were cracked in a fixed-bed microactivity test (MAT) unit and a modified ARCO riser reactor on separate occasions. Several important observations from the MAT study were reported, including the effects of gasoline precursors on the maximum gasoline yields, light cycle oil (LCO) precursors on the optimum LCO yields, and aromatics in feeds on the conversion levels at which the maximum gasoline yields occurred. The yield profiles were similar, in regard to shape and relative position, between H 2 S-free dry gas and catalytic coke for all but one of the feeds. A method to check the qualities of the MAT and riser data was demonstrated by plotting the coke or total gas selectivity versus the gasoline selectivity. Individual yields of gas, liquid, and coke from MAT at conversions of 55, 65, 70, and 81 wt % were compared with their respective pilot-plant data. MAT results, with the exception of coke yield, were, in most cases, within 15% of the corresponding riser yields. Good linear correlations could be established between MAT and riser yields, except for liquefied petroleum gas (LPG) and LCO. Liquid products from MAT were analyzed for hydrocarbon type, sulfur and nitrogen contents, and density, most of which showed good agreement with those obtained from the riser study. The advantages of hydrotreating some poor feeds to improve product yields and qualities were demonstrated and discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".