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Record W2135092483 · doi:10.1002/cjce.21955

Compartmental modelling of turbulent fluid flow for the scale‐up of stirred tanks

2013· article· en· W2135092483 on OpenAlexaffvenue
Hamed Bashiri, Mourad Héniche, François Bertrand, Jamal Chaouki

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRushton turbineImpellerBaffleTurbulenceMechanicsDissipationMixing (physics)Volume (thermodynamics)Constant (computer programming)TurbineAgitatorSCALE-UPVolumetric flow rateFlow (mathematics)Scale (ratio)Work (physics)Computational fluid dynamicsThermodynamicsPhysicsComputer scienceClassical mechanics

Abstract

fetched live from OpenAlex

In this work, the results of single phase CFD simulations of mixing vessels with four baffles agitated by a Rushton turbine are used to determine the parameters of a two‐compartment model that describes the turbulent non‐homogeneities therein. An improved method is proposed to find the boundary between the two characteristic regions. Using this method, the effects of different conventional scale‐up criteria including constant impeller speed, constant impeller tip speed and constant power consumption per liquid volume, on the value of the compartmental model parameters are investigated. It can be observed that the distribution of the turbulent energy dissipation rate and, as a result, the compartmental model parameters change considerably when following conventional scale‐up rules. The concept of a general map of compartment energy dissipation rate and volume ratios, which can be used for the scale‐up of stirred tanks, is introduced.

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 score0.108
Threshold uncertainty score0.341

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 head0.011
GPT teacher head0.169
Teacher spread0.159 · 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

Citations24
Published2013
Admission routes2
Has abstractyes

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