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Record W2154814778 · doi:10.1002/cjce.5450800422

Investigation of Flow Patterns in Continuous‐flow Stirred Vessels by Laser Doppler Velocimetry

2002· article· en· W2154814778 on OpenAlexvenueno aff
P. Mavros, Catherine Xuereb, Ivan Fořt, J. Bertrand

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsnot available
FundersEuropean Commission
KeywordsRushton turbineMechanicsFlow (mathematics)VelocimetryInletMixing (physics)TurbineLaser Doppler velocimetryMaterials scienceResidence time (fluid dynamics)Particle image velocimetryVolumetric flow rateFlow measurementFlow velocityPhysicsTurbulenceMechanical engineeringThermodynamicsGeologyEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The flow structure of a continuous‐flow reactor stirred by a Rushton turbine was investigated by laser Doppler velocimetry for two different mean residence time‐mixing time ratios. Velocity measurements were obtained for two inlet locations, corresponding to the incoming liquid stream being fed co‐currently or counter‐currently to the flow discharged by the turbine. In all investigated configurations and for all operating conditions, it was found that the flow disruption caused by the incoming liquid stream was observable mainly in the first vessel quarter, which followed the feed‐tube plane. From comparison of the velocities encountered in the various planes in the continuous‐flow reactor to the velocities of the batch reactor, it was also concluded that it may be possible to intensify the usage of the turbine‐stirred vessel by decreasing the characteristic times ratio, without considerable flow by‐pass and/or short‐circuiting problems.

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 score0.067
Threshold uncertainty score0.453

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 head0.008
GPT teacher head0.161
Teacher spread0.152 · 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
Published2002
Admission routes1
Has abstractyes

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