Impact of Multiphase Behavior on Coke Deposition in Heavy Oils Hydroprocessing Catalysts
Bibliographic record
Abstract
Coke deposition in heavy oil catalytic hydroprocessing remains a serious problem. The influence of multiphase behavior on coke deposition is an important but unresolved question in this literature. A model mixture comprising Athabasca vacuum bottoms (ABVB) + decane + hydrogen which is shown to exhibit low-density liquid + vapor, high-density liquid + vapor, as well as low-density liquid + high-density liquid + vapor, phase behavior at typical hydroprocessing conditions and a commercial heavy oil hydrotreating catalyst (NiMo/γ-Al 2 O 3 ) were employed in this investigation. The influence of multiphase behavior on coke deposition was explored under catalyst coking conditions (380 °C and 2 h). The liquid−liquid-vapor region extends from ∼20% ABVB to ∼50% ABVB. Coke deposition in the high-density liquid phase was found to be greater than in the low-density liquid phase, at fixed global composition. Conventional kinetics models which do not include the impact of such phase behavior effects cannot account for local maxima in the coke deposition versus coke precursor concentration profiles that result when complex phase behavior is encountered.
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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 | 0.000 | 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".