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Record W4413802041 · doi:10.1016/j.powtec.2025.121606

Investigating gas dispersion and solid suspension in a coaxial stirred tank containing non-Newtonian fluids using coupled tomography and pressure measurements

2025· article· en· W4413802041 on OpenAlexafffund
Ehsan Zamani Abyaneh, Farhad Ein‐Mozaffari, Ali Lohi

Bibliographic record

VenuePowder Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoaxialSuspension (topology)Dispersion (optics)Newtonian fluidMechanicsNon-Newtonian fluidTomographyMaterials scienceGas pressureChromatographyMechanical engineeringEngineeringPetroleum engineeringChemistryPhysicsOpticsMathematics

Abstract

fetched live from OpenAlex

Three-phase agitated tanks are widely utilized across industries such as chemical processing, pharmaceuticals, wastewater treatment, and biotechnology, where precise control over gas, liquid, and solid phases is crucial for process efficiency. Despite their industrial significance, accurate quantification of local gas and solid holdups in such systems remains problematic, primarily due to the limitations of available visualization and measurement techniques. Although electrical resistance tomography (ERT) coupled with pressure measurements has shown efficacy in multiphase systems without rotating parts, its application in mechanically agitated tanks has not been reported. This study presents the first experimental integration of ERT with calibrated pressure measurements in a coaxial mixer containing non-Newtonian fluid, enabling localized quantification of gas and solid holdups under varying non-Newtonian fluid concentrations and evaluating both upward and downward pumping modes of the central impeller. Key findings show that upward pumping enhances solid suspension by promoting particle transport, while downward pumping improves gas dispersion by extending bubble residence time; moreover, liquid rheology strongly shapes holdups, highlighting the interplay between fluid properties and mixing dynamics.

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 score0.976
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.237
Teacher spread0.227 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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