Energy and economical comparison of possible cultures for a total-integrated on-field biodiesel production
Bibliographic record
Abstract
This work is aimed at investigating the energy conversion effectiveness and the economical advantages of a total integrated solution for on-field biodiesel and electrical energy production. The system proposed here is based on the synergy of four sub-systems: a seed press for oil production, a downdraft gasifier, a biodiesel conversion plant and a Solid Oxide Fuel Cell (SOFC). Two possible culture rotations, suggested by literature review, were analyzed here from economical and energy balance points of view. Both the rotations were composed of oleaginous crops only, therefore the seeds collected from the different cultures were pressed, then the protein cake produced in the process was gasified in the downdraft reactor. The gasification process was modeled here, and its output suggested that, for a precise number of hectares, the syngas obtained through the cake gasification was enough for producing methanol required for oil-biodiesel conversion and feeding a 10-kW SOFC. The purge line in the methanol reactor was used in the SOFC as well. The system was simulated using ASPEN PLUS TM and MATLAB TM codes. Results of the SOFC and gasifier models underlined the capability of the fuel cell to work with this particular system, furthermore the whole system analysis suggested that the surface required for sustainability of the processes is a function of the rotation choice. In both cases little surfaces ranging from 11 to 21 hectares were found to be enough for system self-sustainability with a ROI under 7 years in all the operating conditions analyzed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".