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Record W2620635727 · doi:10.1002/cjce.22911

Drop behaviour characteristics in different operating regimes in an L‐shaped pulsed sieve‐plate column

2017· article· en· W2620635727 on OpenAlexvenueno aff
Pouria Amani, Mohamad Esmaieli

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersUniversity of Tehran
KeywordsDrop (telecommunication)MechanicsDispersion (optics)Sieve (category theory)Mass transferChemistryPlate columnMaterials scienceAnalytical Chemistry (journal)ChromatographyThermodynamicsPhysicsOpticsMathematics

Abstract

fetched live from OpenAlex

Abstract In this study, the influence of different operating regimes on drop behaviour in an L‐shaped pulsed sieve‐plate column has been investigated and the effects of pulsation intensity and phase superficial velocities on drop diameters are evaluated. The toluene‐water system with 0.03 L/L (3 vol%) acetone as a mass transfer agent is used. Experimental observations reveal that with increasing pulsation intensity, drop sizes slightly decrease and by reaching to the end of mixer‐settler regime, they significantly decrease followed by a mild decrease in the dispersion regime. Moreover, it is observed that mean drop size firstly varies inversely as both phase superficial velocities change, while it slightly increases with further increase in superficial velocities. Finally, some of the most recommended correlations are compared to the experimental data. It is revealed that these correlations show the highest deviation in the lower end of the mixer‐settler regime (> 40 %), while in the dispersion regime it becomes < 15 %, indicating that they are only applicable in the region of practical regimes. Accordingly, two of these correlations are modified in order to cover different operating regimes by means of two correlations proposed to predict the transition regime in each section of the column. The AARE values of the modified correlations are found to be < 14.7 %.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.596

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 integrity0.0000.001
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 head0.009
GPT teacher head0.199
Teacher spread0.191 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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