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Record W2089806182 · doi:10.1002/cjce.22084

Modelling of pyrolysis in a high capacity thermo balance

2014· article· en· W2089806182 on OpenAlexvenueno aff
Frédéric Marías, Stéphanie Delage Santacreu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
FundersUniversité de Pau et des Pays de l'Adour
KeywordsPyrolysisCharMaterial balanceBiomass (ecology)Volume (thermodynamics)Mass transferWater contentThermalMaterials scienceTransient (computer programming)Process engineeringEnvironmental scienceMechanicsThermodynamicsComputer scienceWaste managementEngineeringPhysicsGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract This paper deals with the two dimensional modelling of transient pyrolysis of biomass in a fixed bed. The model that is developed mainly relies on the theory of volume averaging. This model includes heat and mass transfer and pyrolysis reaction. It allows the prediction of temperature, moisture content organic material content, and char content, as well as the prediction of internal evolution of the composition of the gas held and released from the sample under investigation. This model is used in order to describe pine wood pyrolysis taking place in a macro thermobalance which is also presented in the paper. Comparison of the numerical results with the experimental ones, in terms of mass loss of the sample, shows good agreement and validates the model. A deeper analysis of the results allows a better understanding of the processes involved in the thermal degradation.

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 score0.276
Threshold uncertainty score0.399

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 head0.009
GPT teacher head0.153
Teacher spread0.144 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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