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Record W4382940492 · doi:10.1002/cjce.25037

Experimental investigation of bubble size evolution released from a fine bubble ejector

2023· article· en· W4382940492 on OpenAlexvenueno aff
Jinliang Tao, Jiao Li, Qingshan Huang, Hang Xiao, Huidong Zhang, Aqiang Chen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersChinese Academy of SciencesNational Natural Science Foundation of ChinaNatural Science Foundation of Shandong ProvinceShandong Energy Institute, Chinese Academy of Sciences
KeywordsBubbleCoalescence (physics)InjectorSurface tensionMaterials scienceVolumetric flow rateViscosityMechanicsTap waterThermodynamicsChemistryComposite materialEnvironmental engineeringPhysicsEnvironmental science

Abstract

fetched live from OpenAlex

Abstract The effects of gas flow rate, liquid flow rate, and liquid properties on the bubble size evolution at the outlet zone of an ejector have been investigated systemically. The liquid properties, including surface tension and viscosity, were changed by adding glycerol, ethanol, or Carbopol 2020 into tap water. It was found that increasing the liquid flow rate is beneficial for producing smaller bubbles with a narrower size distribution in the ejector, while the gas flow rate investigated here shows less influence on the generated fine bubble diameter. An intense bubble coalescence phenomenon, which has a negative effect on mass transfer, was first observed at the small outlet zone of the ejector by exploring the bubble size evolution along the axial height. It was found that the mean diameter of the fine bubbles could increase by 48% ~ 90% when they rose only 25 cm from the ejector outlet, and the bubble coalescence could be effectively suppressed by adding a small amount of glycerol to water. The bubble diameter could be reduced by 32% ~ 43% by using a 2 wt.% glycerol solution under the experimental conditions. A comparative study with tap water, glycerol solution, Carbopol solution, and ethanol solution was taken, and the underlying mechanism of reducing the generated bubble size by changing the liquid properties was revealed.

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 score0.271
Threshold uncertainty score0.388

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 head0.006
GPT teacher head0.168
Teacher spread0.162 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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