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Record W2149477305 · doi:10.1002/ceat.200800565

Mapping of the Operating Conditions for an Interconnected Fluidized Bed Reactor for CO<sub>2</sub> Separation by Chemical Looping Combustion

2009· article· en· W2149477305 on OpenAlexaff
Mingyu Xu, Naoko Ellis, C. Jim Lim, Ho Jin Ryu

Bibliographic record

VenueChemical Engineering & Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsUniversity of British Columbia
FundersMinistry of Economy
KeywordsChemical looping combustionCombustionFluidized bedNuclear engineeringChemical reactorProcess engineeringFluidized bed combustionFluidizationAir separationWaste managementChemistryOxygenEnvironmental scienceChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract As a promising way of integrating combustion, CO2 separation, and pollution control with high efficiency and low cost, Chemical Looping Combustion (CLC) has gained attention in recent years. A cold model circulating fluidized bed reactor for chemical looping combustion was designed and operated, in which an additional loop was used to transfer back some oxygen carriers to the air reactor directly for continuous oxidation. Operating conditions of the cold model were investigated as the superficial gas velocities in the reactors and seal‐loops were varied. Their effects on the pressure balance and solids circulation rates in two loops were tested. The experimental results provided a detailed mapping of the range of operating conditions and assisted in the understanding of critical variables controlling the operation of the CLC reactor system. The appropriate operating conditions were optimized for developing the reactor model for CLC.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.237
Teacher spread0.229 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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