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Record W2078532163 · doi:10.1002/cjce.20161

Numerical simulation of a spouted bed with a draft tube with and without liquid spray

2009· article· en· W2078532163 on OpenAlexafffundvenue
Tingwen Li, Konstantin Pougatch, M. Salcudean, Dana Grecov

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of British Columbia
FundersSyncrude
KeywordsDraft tubeNozzleMechanicsFluentSpray nozzleSpray characteristicsComputational fluid dynamicsMaterials scienceComputer simulationEulerian pathMultiphase flowFlow (mathematics)ThermodynamicsPhysicsLagrangian

Abstract

fetched live from OpenAlex

Abstract Numerical simulations of the gas–solid flow in a flat‐based spouted bed with a draft tube (DTSB) are conducted with a Eulerian–Eulerian granular kinetic model. The hydrodynamics of the flow in DTSB is investigated and compared with published experimental data. The effect of the gas velocity on the particles circulation rate is evaluated, and parametric studies of the restitution coefficient are performed. In addition, several different frictional models are tested. A model for the liquid spray injection into a gas–solid flow is proposed and implemented into a commercial CFD solver, Fluent 6.3. The liquid spray introduced through the bottom nozzle is simulated, and the influence of spray rate on solids concentration and velocity inside the draft tube is examined.

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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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

Citations9
Published2009
Admission routes3
Has abstractyes

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