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Record W2611796941 · doi:10.1002/cjce.22879

Study of fluid dynamic conditions in the selected static mixers part II‐determination of the residence time distribution

2017· article· en· W2611796941 on OpenAlexvenueno aff
Magdalena Stec, P. Synowiec

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsResidence time distributionLaminar flowStatic mixerPlug flowMechanicsMixing (physics)TurbulenceLaminar flow reactorReynolds numberFlow (mathematics)Residence time (fluid dynamics)Work (physics)MathematicsSimulationOpen-channel flowPhysicsComputer scienceThermodynamicsEngineering

Abstract

fetched live from OpenAlex

Abstract The presented paper is part of the complete description of fluid‐dynamic conditions in the selected static mixers: Koflo and Kenics. The research was also performed for an empty pipe used as a reference state. The scope of work included the analysis of the residence time distribution in the mentioned devices for different Reynolds numbers for both laminar and turbulent flow regimes. The report contains a discussion about residence time distribution function E(t) , cumulative distribution function F(t) , as well as the parameters like the mean residence time t m and the variance σ 2 . The main aim of the presented work was to show the applicability of static mixers as chemical reactors and to present their operation characteristics to evaluate the derogations distinguishing them from well known ideal states (i.e. plug flow or ideal mixing). As a result of the accomplished study it was proved that Reynolds number increase results in narrower RTD in all of the tested devices, however the fluid motion is far from plug flow due to axial and radial mixing and the considered equipment should be treated as non‐ideal reactors requiring some additional models for the right description. What is more, in the case of laminar flow, the Kenics static mixer showed the narrowest spread and was considered as the best solution among the studied devices. In the turbulent flow, the difference between E(t) functions for all of the mentioned equipment was so small that the suggestion of small impact of insert type on the RTD was made.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.218

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 science0.0010.000
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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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
Published2017
Admission routes1
Has abstractyes

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