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Record W2104209218 · doi:10.2172/825383

COMPUTATIONAL AND EXPERIMENTAL MODELING OF SLURRY BUBBLE COLUMN REACTORS

2000· report· en· W2104209218 on OpenAlexaboutno aff
Paul C. Lam, Dimitri Gidaspow

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceMechanicsComputational fluid dynamicsTurbulence kinetic energyParticle (ecology)FluidizationFlow (mathematics)SlurryBubbleMaterials scienceTurbulence modelingTwo-phase flowWork (physics)Multiphase flowReynolds stressKinetic energyReynolds numberViscosityThermodynamicsPhysicsFluidized bedGeologyClassical mechanics

Abstract

fetched live from OpenAlex

The objective if this study was to develop a predictive experimentally verified computational fluid dynamics (CFD) model for gas-liquid-solid flow. A three dimensional transient computer code for the coupled Navier-Stokes equations for each phase was developed. The principal input into the model is the viscosity of the particulate phase which was determined from a measurement of the random kinetic energy of the 800 micron glass beads and a Brookfield viscometer. The computed time averaged particle velocities and concentrations agree with PIV measurements of velocities and concentrations, obtained using a combination of gamma-ray and X-ray densitometers, in a slurry bubble column, operated in the bubbly-coalesced fluidization regime with continuous flow of water. Both the experiment and the simulation show a down-flow of particles in the center of the column and up-flow near the walls and nearly uniform particle concentration. Normal and shear Reynolds stresses were constructed from the computed instantaneous particle velocities. The PIV measurement and the simulation produced instantaneous particle velocities. The PIV measurement and the simulation produced similar nearly flat horizontal profiles of turbulent kinetic energy of particles. This phase of the work was presented at the Chemical Reaction Engineering VIII: Computational Fluid Dynamics, August 6-11, 2000 in Quebec City, Canada. To understand turbulence in risers, measurements were done in the IIT riser with 530 micron glass beads using a PIV technique. The results together with simulations will be presented at the annual meeting of AIChE in November 2000.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.681

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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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 teacher head, 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

Citations1
Published2000
Admission routes1
Has abstractyes

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