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Record W1973964587 · doi:10.1002/cjce.5450780119

Three‐stage well‐mixed reactor model for a pressurized coal gasifier

2000· article· en· W1973964587 on OpenAlexafffundvenueabout
B. H. Song, A. P. Watkinson

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCharWood gas generatorCoaltar (computing)Isothermal processCarbon fibersCoal gasificationCombustionSorbentCoal rankDecompositionWaste managementChemical engineeringChemistryEnvironmental scienceMaterials scienceThermodynamicsEngineeringOrganic chemistryAdsorptionComposite material

Abstract

fetched live from OpenAlex

Abstract Three Canadian coals of different rank were gasified with air‐steam mixtures in a 0.1 m diameter spouted bed reactor at pressures to 292 kPa, average bed temperatures varying between 840 and 960°C, and steam‐to‐coal feed ratios between 0.0 and 2.88. In order to analyze gasifier performance and correlate data, a three‐stage model has been developed incorporating instantaneous devolatilization of coal, instantaneous combustion of carbon at the bottom of the bed, and steam/carbon gasification and water gas shift reaction in a single well mixed isothermal stage. The capture of H2S by limestone sorbent injection is also treated. The effects of various assumptions and model parameters on the predictions were investigated. The present model indicates that gasifier performance is mainly controlled by the fast coal devolatilization and char combustion reactions, and the contribution to carbon conversion of the slow char gasification reactions is comparatively small. The incorporation of tar decomposition into the model provides significantly closer predictions of experimental gas composition than is obtained otherwise.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.183
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations14
Published2000
Admission routes4
Has abstractyes

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