Optimum scale of feedstock processing for renewable diesel production
Bibliographic record
Abstract
Abstract Vegetable oil from canola and camelina can be converted to renewable diesel via hydroprocessing. In this study, a techno‐economic model was developed to estimate the cost of vegetable oil production and the production plant economic optimum size using canola or camelina as feedstock. Minimum, average, and maximum yield cases were considered. If canola and camelina meal can be sold for $0.26/kg, in the average yield case the optimum plant size and minimum cost of oil production is 140 million L/year and $0.63/L for a canola‐press plant, 190 million L/year and $0.55/L for a canola‐solvent plant, 90 million L/year and $0.28/L for a camelina‐press plant, and 120 million L/year and $0.28/L for a camelina‐solvent plant. If camelina meal cannot be sold, the cost of oil from camelina‐press and solvent plants at their optimum sizes is $1.04/L and $0.82/L, respectively. Field cost is the largest cost component and it makes up 75–85% of the total oil production cost. A sensitivity analysis found that field cost and meal price have the greatest effect on oil cost; the optimum size of the plant, on the other hand, is most sensitive to transportation, capital, and operating and maintenance costs. © 2012 Society of Chemical Industry and John Wiley & Sons, Ltd
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".