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Record W2025028837 · doi:10.1021/ie0607548

Using Computational Fluid Dynamics Modeling and Ultrasonic Doppler Velocimetry To Study Pulp Suspension Mixing

2007· article· en· W2025028837 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2007
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputational fluid dynamicsImpellerMechanicsFluentVelocimetryParticle image velocimetryMixing (physics)RheologyUltrasonic sensorMaterials scienceLaser Doppler velocimetryMechanical engineeringAcousticsTurbulencePhysicsEngineeringComposite materialBlood flow

Abstract

fetched live from OpenAlex

In this study, the flow field of a cylindrical pulp mixing chest equipped with a side-entering impeller was modeled using commercial computational fluid dynamics (CFD) software (Fluent) with the rheology of the pulp suspension approximated using the Herschel−Bulkley model. To validate the model, CFD results for the power and velocity field were compared to experimental data. Ultrasonic Doppler velocimetry (UDV), a noninvasive fluid flow measurement technique for opaque systems, was used to measure pulp suspension velocity. In order to calculate the mixing time, an unsteady state solver in Fluent was applied to monitor the tracer species concentration as a function of time in the tank. The validated CFD model provided useful information regarding the mixing time and the formation of the cavern around the impeller in the mixing of pulp suspension. The size of cavern predicted by the CFD model was in good agreement with that calculated using Solomon's model.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.136
GPT teacher head0.342
Teacher spread0.206 · 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