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Record W3163798384 · doi:10.1002/ceat.202000262

Mixing Time and Scale‐up Investigation of a Moving‐Baffle Oscillatory Baffled Column

2021· article· en· W3163798384 on OpenAlex
Kayte Sutherland, Leila Pakzad, Pedram Fatehi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemical Engineering & Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsLakehead University
Fundersnot available
KeywordsBaffleDimensionless quantityMixing (physics)MechanicsSCALE-UPOscillation (cell signaling)Scale (ratio)Reynolds numberWork (physics)AmplitudeColumn (typography)PaddleComputational fluid dynamicsMaterials scienceChemistryPhysicsThermodynamicsMathematicsClassical mechanicsTurbulenceGeometryOpticsComposite material

Abstract

fetched live from OpenAlex

Abstract Mixing time and scale‐up behavior were investigated for a moving‐baffle oscillatory baffled column (MB‐OBC). Computational fluid dynamics software was used to investigate the effects of the oscillation conditions and changes in the column scale on the dimensionless mixing time. The results indicate that small amplitudes combined with high frequencies are detrimental to the mixing efficiency and that the scale‐up of an MB‐OBC is linearly dependent on the column diameter. This work, in combination with previous studies, proves that the predictability of the hydrodynamic behavior during scale‐up is inherent to oscillatory baffled columns. This trait is desirable for adapting these columns for industrial‐scale applications.

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.

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 score0.407
Threshold uncertainty score0.803

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 head0.003
GPT teacher head0.155
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