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Record W2046101269 · doi:10.1080/0986440490472599

CFD SIMULATION AND EXPERIMENTAL STUDY OF FLOW IN PACKED BUBBLE COLUMNS

2004· article· en· W2046101269 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Engineering Communications · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBubblePacked bedMechanicsComputational fluid dynamicsDragVolumetric flow rateFlow (mathematics)Volume (thermodynamics)Materials scienceThermodynamicsSPHERESChemistryChromatographyPhysics

Abstract

fetched live from OpenAlex

The gas holdup in a small-scale packed bubble column with dimensions of 35 mm wide and 10 mm deep was measured for air-water system. The effect of gas flow rate on gas holdup was investigated for various packings such as spheres, Berl saddles, and knitted meshes. In all cases it was found that the gas holdup increases with increasing gas flow rate. In addition, bubble size distribution was measured from image analysis. The hydrodynamics in the packed bubble column was simulated using volume-averaged equations. The closure models for describing the flow resistance due to the presence of packing particles and interphase drag force between gas bubbles and liquid phase were incorporated into the volume-averaged equations. The simulations were conducted under experimental conditions using the commercial CFD software CFX4.3. Good agreement between the simulation results and the experimental data indicates that CFD simulation can play a useful role in the analysis and design of packed bubble columns.

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.

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 score0.114
Threshold uncertainty score0.425

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 head0.013
GPT teacher head0.250
Teacher spread0.236 · 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