MétaCan
Menu
Back to cohort
Record W2020138646 · doi:10.1002/cjce.20295

A simple method for identifying bubbling/jetting regimes transition from large submerged orifices using electrical capacitance tomography (ECT)

2010· article· en· W2020138646 on OpenAlexvenueno aff
Qingbai Cai, Xuesong Shen, Chunyin Shen, Gance Dai

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersEast China University of Science and Technology
KeywordsBody orificeDimensionless quantityReynolds numberMaterials scienceCapacitanceMechanicsElectrical capacitance tomographyPhase transitionAnalytical Chemistry (journal)ThermodynamicsChemistryPhysicsChromatographyMechanical engineeringTurbulenceEngineering

Abstract

fetched live from OpenAlex

Abstract The bubbling–jetting transition regimes from large orifice submerged in water were investigated for various orifice diameters. A simple and fast way for identifying the regime transition was successfully developed using electrical capacitance tomography (ECT). In all the experiments deionised water was liquid phase and air was gas phase. Orifice gas velocity ( V N ) and orifice diameter ( d o ) were varied from 0.8 to 186 m/s and 4–21 mm, respectively. It was found that the V N,trans. strongly depends on the orifice diameter. In the small orifice diameter ( d o < 10 mm), V N,trans. greatly decreases with the increase of orifice diameter. However, in the large orifice diameter ( d o > 10 mm), the effect of orifice diameter on the transition velocity is insignificant. Finally, the data obtained by ECT compares with other works and the dimensionless orifice Reynolds number (Re o ∼11,000) is preferred to identify the bubbling–jetting transition regimes.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.010
GPT teacher head0.227
Teacher spread0.216 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicFluid Dynamics and MixingFrench-language works237,207