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Record W2036567281 · doi:10.1002/cjce.5450830209

A Combined Mass Transfer Coefficient Model for Liquid-Liquid Systems under Simultaneous Effect of Contamination and Agitation

2008· article· en· W2036567281 on OpenAlexvenueno aff
Javad Saien, Mohammad Barani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsMass transfer coefficientPhysicsMass transferThermodynamics

Abstract

fetched live from OpenAlex

The simultaneous effect of contamination and agitation was investigated using a pilot rotating disc contactor and mass transfer in both directions with single drops in the absence of drop break-up and coalescence. It is ideally required to account for the extent of contamination in a quantitative manner and in both phases with a single parameter. In this work, a combined mass transfer model is applied and an improvement is made using an empirical coefficient and having mathematical consistency. Based on 120 experimental data series obtained for each mass transfer direction, a correlation is proposed for the coefficient of this model. On a étudié l'effet simultané de la contamination et de l'agitation à l'aide d'un contacteur à disque rotatif pilote et du transfert de matière dans les deux directions avec des gouttes uniques en l'absence de rupture et coalescence de gouttes. Il faut idéalement prendre en compte la portée de la contamination d'une manière quantitative et dans les deux phases avec un seul paramètre. Dans ce travail, on applique un modèle de transfert de matière combiné et on apporte une amélioration en utilisant un coefficient empirique et en ayant une cohérence mathématique. D'après 120 séries de données expérimentales obtenues pour chaque direction de transfert de matière, une corrélation est proposée pour le coefficient de ce modèle.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.367

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 head0.176
Teacher spread0.170 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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