Kinetics of Cracking and Devolatilization during Coking of Athabasca Residues
Bibliographic record
Abstract
The kinetics of cracking, coking, and devolatilization of Athabasca bitumen were investigated by reacting thin films of feed material. Samples of vacuum residue (524 °C+), scrubber bottoms, and residue from a batch fluid coker were reacted in films of thickness 20 μm on strips of Curie-point alloy. The strips were heated to temperatures of 457, 503, and 530 °C in a nitrogen atmosphere using an induction furnace. After reaction, the remaining unconverted liquid was extracted from the films, the toluene-insoluble residue was weighed, and the condensed vapor and extract liquids were analyzed for microcarbon residue content (MCR) and boiling distribution by simulated distillation. The kinetics of reaction and devolatilization were consistent with a lumped kinetic model that included cracking, coke formation, and vaporization limited by equilibrium ratios and mass transfer. The kinetic model was able to reproduce the experimental data for total extractable and coke yield as a function of time, as well as the yields of residue and gas oil fractions in the vapor product and remaining in the liquid film. Even though the heavy residue fractions had equilibrium ratios of less than 0.01, 10−15 wt % of the feed appeared in the vapor product as 650 °C+ material. MCR content correlated well with the fraction of 650 °C+ material; therefore, the model predictions were consistent with the MCR content of the vapor products.
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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".