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Record W2328537540 · doi:10.1515/1542-6580.3049

New Correlations of Volumetric Liquid-Phase Mass Transfer Coefficients in Gas-Inducing Agitated Tank Reactors

2012· article· en· W2328537540 on OpenAlexaff
Hesheng Yu, Zhongchao Tan

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsImpellerMass transferMass transfer coefficientVolume (thermodynamics)Dispersion (optics)MechanicsThermodynamicsLiquid phaseRange (aeronautics)Phase (matter)Materials scienceLiquid liquidChemistryAnalytical Chemistry (journal)ChromatographyPhysicsComposite materialOptics

Abstract

fetched live from OpenAlex

Abstract Volumetric liquid-phase mass transfer coefficient (kLa) is one of the most important parameters for the evaluation of the performance of a gas-inducing agitated tank (GIAT). In this paper, two equations in terms of power input per unit liquid volume (P/VL) and relative gas dispersion parameter (NI/Ncd), respectively, are developed according to data in literature. They can correlate existing kLa values within ±20% of measured ones for bladed impellers with different impeller submergence to tank diameter ratios in the range of 0.5 -1.23. In order to validate these equations, the liquid phase mass transfer coefficients in a continuous GIAT equipped with a 4-blade straight impeller were measured by removal of oxygen from water. It was found that the equation in P/VL criterion could correlate kLa values within ±12% of the experimental data, and the equation in NI/Ncd criterion could correlate kLa values within ±15.6% with an exception of 26.8% for NI = 16.7 Hz.

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 score0.233
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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