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Effect of oxygen presence in torrefier

2013· article· en· W1996335761 on OpenAlexaff
Pallab Basu, Alok Dhungana, Shailendra Rao, Bishnu Acharya

Bibliographic record

VenueJournal of the Energy Institute · 2013
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsGreenfield Research (Canada)Dalhousie University
Fundersnot available
KeywordsOxygenYield (engineering)Limiting oxygen concentrationInert gasNitrogenChemistryTorrefactionBiomass (ecology)Work (physics)DecompositionAtmosphere (unit)Pulp and paper industryMaterials scienceThermodynamicsOrganic chemistryMetallurgyAgronomy

Abstract

fetched live from OpenAlex

Torrefaction, though defined as a low temperature (200–300°C) decomposition of biomass in an oxygen free atmosphere, it is hard to obtain such environment in a commercial unit unless one uses expensive means of nitrogen flushing or indirect heating. Oxygen leakage that adversely affects the product quality is unavoidable in commercial directly heated torrefier. Present work attempts to examine the optimum concentration of oxygen in the torrefier that can be tolerated without greatly compromising the product quality. In this work, torrefaction of relatively large pieces (25·4 and 19 mm diameter) of poplar wood was conducted at different oxygen concentration as well as in inert atmosphere while observing its effect on the temperature profile in the biomass interior, mass yield, energy yield and energy density. Results obtained are in agreement with those obtained in previous work on fine biomass particles that mass yield and energy yield decreases with oxygen presence in the torrefier. It, however, notes a slight increase in energy density. The work observes a sharp decline in mass yield beyond about 14% oxygen concentration suggesting that this may be the practical limit of oxygen in a torrefier. Finally this work notes that the presence of modest amount of oxygen could not only be tolerated but it may have some positive effect on the commercial design of a torrefier.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.171

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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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