Laboratory Production of Biofuels and Biochemicals from a Rapeseed Oil through Catalytic Cracking Conversion
Bibliographic record
Abstract
The work is based on a reported study which investigates the processability of canola oil (bio-feed) in the presence of bitumen-derived heavy gas oil (HGO) for production of transportation fuels through a fluid catalytic cracking (FCC) route. Cracking experiments are performed with a fully automated reaction unit at a fixed weight hourly space velocity (WHSV) of 8 hr(-1), 490-530 °C, and catalyst/oil ratios of 4-12 g/g. When a feed is in contact with catalyst in the fluid-bed reactor, cracking takes place generating gaseous, liquid, and solid products. The vapor produced is condensed and collected in a liquid receiver at -15 °C. The non-condensable effluent is first directed to a vessel and is sent, after homogenization, to an on-line gas chromatograph (GC) for refinery gas analysis. The coke deposited on the catalyst is determined in situ by burning the spent catalyst in air at high temperatures. Levels of CO2 are measured quantitatively via an infrared (IR) cell, and are converted to coke yield. Liquid samples in the receivers are analyzed by GC for simulated distillation to determine the amounts in different boiling ranges, i.e., IBP-221 °C (gasoline), 221-343 °C (light cycle oil), and 343 °C+ (heavy cycle oil). Cracking of a feed containing canola oil generates water, which appears at the bottom of a liquid receiver and on its inner wall. Recovery of water on the wall is achieved through washing with methanol followed by Karl Fischer titration for water content. Basic results reported include conversion (the portion of the feed converted to gas and liquid product with a boiling point below 221 °C, coke, and water, if present) and yields of dry gas (H2-C2's, CO, and CO2), liquefied petroleum gas (C3-C4), gasoline, light cycle oil, heavy cycle oil, coke, and water, if present.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".