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Energy and economical comparison of possible cultures for a total-integrated on-field biodiesel production

2014· article· en· W2078715135 on OpenAlexaff
Giulio Allesina, Simone Pedrazzi, Sina Tebianian, Alberto Muscio, Paolo Tartarini

Bibliographic record

VenueJournal of Physics Conference Series · 2014
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiodieselWood gas generatorSyngasBiodiesel productionProcess engineeringWork (physics)Waste managementProcess (computing)Environmental scienceSolid oxide fuel cellEngineeringMechanical engineeringComputer scienceChemistry

Abstract

fetched live from OpenAlex

This work is aimed at investigating the energy conversion effectiveness and the economical advantages
\nof a total integrated solution for on-field biodiesel and electrical energy production. The system proposed
\nhere is based on the synergy of four sub-systems: a seed press for oil production, a downdraft gasifier, a
\nbiodiesel conversion plant and a Solid Oxide Fuel Cell (SOFC). Two possible culture rotations, suggested
\nby literature review, were analyzed here from economical and energy balance points of view. Both the
\nrotations were composed of oleaginous crops only, therefore the seeds collected from the different cultures
\nwere pressed, then the protein cake produced in the process was gasified in the downdraft reactor. The
\ngasification process was modeled here, and its output suggested that, for a precise number of hectares, the
\nsyngas obtained through the cake gasification was enough for producing methanol required for oil-biodiesel
\nconversion and feeding a 10-kW SOFC. The purge line in the methanol reactor was used in the SOFC as
\nwell. The system was simulated using ASPEN PLUSTMand MATLABTMcodes. Results of the SOFC and
\ngasifier models underlined the capability of the fuel cell to work with this particular system, furthermore the
\nwhole system analysis suggested that the surface required for sustainability of the processes is a function
\nof the rotation choice. In both cases little surfaces ranging from 11 to 21 hectares were found to be enough
\nfor system self-sustainability with a ROI under 7 years in all the operating conditions analyzed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.259
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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