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Record W1965650883 · doi:10.1002/cjce.5450810344

Using CFD to Describe the Hydrodynamics of Internal Air‐lift Reactors

2003· article· en· W1965650883 on OpenAlexvenueno aff
Jasper M. van Baten, J. Ellenberger, Rajamani Krishna

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsComputational fluid dynamicsMechanicsTurbulenceLift (data mining)DragRange (aeronautics)Materials sciencePhysicsComputer science

Abstract

fetched live from OpenAlex

Abstract The hydrodynamics of three configurations of internal airlift reactors, two with riser diameters of 0.1 m and one with a riser diameter of 0.24 m, operating with air—water system, have been experimentally investigated for a range of superficial gas velocities. The experimental results are compared with a model using computational fluid dynamics (CFD) with Eulerian descriptions of the gas and liquid phases. Interactions between the bubbles and the liquid are taken into account by means of a momentum exchange, or drag coefficient based on a literature correlation. The turbulence in the liquid phase is described using the k ‐ϵ model. The CFD model shows good agreement with the measured data on gas holdup, liquid velocity in the downcomer and in the riser for all three configurations. The developed CFD model has the potential of being applied as a tool for scaling up.

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 score0.096
Threshold uncertainty score0.417

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 head0.009
GPT teacher head0.182
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 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

Citations22
Published2003
Admission routes1
Has abstractyes

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