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Record W2049923883 · doi:10.1021/ie9004892

Experimental and Computational Fluid Dynamics Study of Dense-Phase, Transition Region, and Dilute-Phase Spouting

2009· article· en· W2049923883 on OpenAlexaff
Marcos A.S. Barrozo, Cláudio R. Duarte, Norman Epstein, John R. Grace, C. Jim Lim

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2009
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of British Columbia
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsAnnulus (botany)MechanicsPhase (matter)Work (physics)Particle (ecology)Materials scienceFlow (mathematics)Phase transitionTwo-phase flowThermodynamicsChemistryPhysicsGeologyComposite material

Abstract

fetched live from OpenAlex

In this work, the transition between conventional dense-phase spouting and dilute-phase spouting is quantified and characterized on the basis of experimental particle velocity and bed voidage data, obtained with an optical fiber probe, as well as from the evolution of pressure with air velocity. The high gas velocities associated with the dilute-phase spouted bed (DSB) flow regime result in voidages exceeding 0.9 over the entire bed, with no discernible distinction between spout and annulus. The downward particle velocities for the DSB regime differ in magnitude from those in the dense-phase spouting regime. Computational fluid dynamics simulations using the Eulerian granular multiphase model show good agreement with experimental data for the three reproducible flow regimes: dense-phase spouting, transition regime, and dilute-phase spouting.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.051
GPT teacher head0.329
Teacher spread0.278 · 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

Citations47
Published2009
Admission routes1
Has abstractyes

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