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Record W2326121378 · doi:10.1021/ef4011109

Some Combustion Characteristics of Biomass and Coal Cofiring under Oxy-Fuel Conditions in a Pilot-Scale Circulating Fluidized Combustor

2013· article· en· W2326121378 on OpenAlexafffund
Yewen Tan, Lufei Jia, Yinghai Wu

Bibliographic record

VenueEnergy & Fuels · 2013
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsNatural Resources Canada
FundersNatural Resources Canada
KeywordsCofiringFlue gasCombustionCoalCombustorWaste managementBiomass (ecology)Fluidized bed combustionPelletsEnvironmental scienceBituminous coalFlue-gas emissions from fossil-fuel combustionSolid fuelChemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

A series of tests were conducted using CanmetENERGY’s pilot-scale, oxy-fuel firing capable circulating fluidized bed (CFB) combustor. These tests were done with a variety of coals, ranging from lignite to bituminous, that were cofired with biomass, specifically wood pellets. The amount of cofired wood pellets varied from 20 to 50% by weight. The objectives of these tests were to measure the combustion characteristics of oxy-fuel cofiring with coal and biomass, including flue gas composition, emissions of volatile organic compounds, and emissions of trace metals. Test results showed that stable combustion conditions could be obtained with a CO 2 concentration in the flue gas of >90% and that the addition of wood pellets did not appreciably affect combustion conditions. These results provided support for the claim that cofiring solid fossil fuels such as coal and coke with carbon-neutral biomass under oxy-fuel conditions with CO 2 capture is a sound approach for achieving negative CO 2 emissions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.204
Teacher spread0.194 · 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 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

Citations43
Published2013
Admission routes2
Has abstractyes

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