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Record W2153429450 · doi:10.1002/aic.12725

Bubble behavior in corrugated‐wall bubbling fluidized beds—Experiments and CFD simulations

2011· article· en· W2153429450 on OpenAlexafffund
Alam Nawaz Khan Wardag, F. Larachi

Bibliographic record

VenueAIChE Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsPakistan Institute of Engineering and Applied Sciences
KeywordsFluidizationBubbleMechanicsSluggingPressure dropCoalescence (physics)Fluidized bedComputational fluid dynamicsMaterials scienceFlow (mathematics)ThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract A new concept to harness bubble dynamics in bubbling fluidization of Geldart D particles was proposed. Various geometrical declinations of a cold‐prototype corrugated‐wall bubbling fluidized bed were compared at different flow rates ( U g ) to conventional flat‐wall fluidized bed using high‐speed digital image analysis. Hydrodynamic studies were carried out to appraise the effect of triangular‐shaped wall corrugation on incipient fluidization, bubble coalescence (size and frequency), bubble rise velocity, and pressure drop. Bubble size and rise velocity in corrugated‐wall beds were appreciably lower, at given U g / U mb , than in flat‐wall beds with equal flow cross‐sectional areas and initial bed heights. The decrease (increase) in size (frequency) of bubbles during their rise was sustained by their periodic breakups while protruding through the necks between corrugated plates. Euler‐Euler transient full three‐dimensional computational fluid dynamic simulations helped shape an understanding of the impact of corrugation geometry on lowering the minimum bubbling fluidization and improving gas distribution. © 2011 American Institute of Chemical Engineers AIChE J, 2012

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.672

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 head0.035
GPT teacher head0.245
Teacher spread0.210 · 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 designBench or experimental
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

Citations16
Published2011
Admission routes2
Has abstractyes

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