MétaCan
Menu
Back to cohort
Record W2002949847 · doi:10.1002/cjce.5450780201

New image analysis methods for the study of mixing patterns in stirred tanks

2000· article· en· W2002949847 on OpenAlexvenueno aff
Fabrice Guillard, Christian Trägårdh, László Fuchs

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsImpellerMixing (physics)PlanarPlanar laser-induced fluorescenceOscillation (cell signaling)Mixing patternsMechanicsTransformation (genetics)Lagrangian coherent structuresBinary numberScale (ratio)Topology (electrical circuits)PhysicsVortexControl theory (sociology)Biological systemLaserOpticsComputer scienceMathematicsChemistryLaser-induced fluorescenceArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Abstract A method of treating data acquired with the planar laser‐induced fluorescence technique has been developed to visualize the topology of two‐dimensional concentration fields and to describe the dynamics of the coherent mixing structures identified. This method is based on a conditional binary transformation of the local concentration data, combined with a joint probability calculation. The methodology has been used to investigate the mixing in a stirred tank, at two injection port locations (in the bulk and in the impeller stream region). With bulk injection, a “folding phenomenon” of the coherent mixing structure was detected. Away from this port, large‐scale spatially periodic motion was identified, with a characteristic time of oscillation of the order of 2 to 3 s. With injection in the impeller stream region, no spatial instabilities of the coherent structure were detected. Local oscillations of the coherent mixing structure were found both on short and long time‐scales (i.e., ˜1 and ˜80 s).

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)0.001
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 score0.151
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.241
Teacher spread0.233 · 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

Citations15
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicFluid Dynamics and MixingFrench-language works237,207