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Record W2048765749 · doi:10.1002/cjce.5450780610

High temperature desulphurization by fine limestone during staged fluidized‐bed combustion

2000· article· en· W2048765749 on OpenAlexvenueno aff
Wasi Z. Khan, Bernard M. Gibbs

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsSorbentCombustionCombustorFluidized bed combustionFluidized bedCoalElutriationMolar ratioStaged combustionStoichiometryMineralogyCoal combustion productsMaterials scienceChemistryMetallurgyWaste managementCombustion chamberAdsorption

Abstract

fetched live from OpenAlex

Abstract This paper reviews the SO 2 emission from a 0.3 m 2 stainless‐steel fluidized‐bed combustor. Fine coal was premixed with fine limestone and fed pneumatically under the bed. The SO 2 emission was found to depend largely on air staging ratio and bed temperature, which agrees with previous observations. The SO 2 emission observed in sorbent‐free tests (reported earlier by Khan and Cibbs, 1995) was found to be proportional to the sulphur content of the fuel when limestone was added, the sulphur capture at a fixed Ca/S molar ratio was dependent on oxygen stoichiometry and bed temperature. Finely sized limestone enhanced the effectivity of the sorbent at low bed temperature and air staging ratio. During staged combustion, the combustion efficiency depended largely on primary air to coal ratio. Around 90% combustion efficiency was observed at 1 m/s fluidizing velocity which was reduced when fluidizing velocity was increased to 1.5 and 2 m/s. This reduction is due to increased elutriation of finer coal particles from the combustor.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.009
Threshold uncertainty score0.676

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 head0.003
GPT teacher head0.150
Teacher spread0.147 · 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

Labeled directly by 2 models reading the full record.

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
Published2000
Admission routes1
Has abstractyes

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