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Record W2040318558 · doi:10.1088/1757-899x/42/1/012048

Using ultrasonic Doppler velocimetry to investigate the mixing of non-Newtonian fluids

2012· article· en· W2040318558 on OpenAlex
Dineshkumar Patel, Farhad Ein‐Mozaffari, Mehrab Mehrvar

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

VenueIOP Conference Series Materials Science and Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsShear thinningXanthan gumRheologyImpellerNon-Newtonian fluidNewtonian fluidVelocimetryLaser Doppler velocimetryMaterials scienceUltrasonic sensorMixing (physics)Complex fluidMechanicsComposite materialPhysicsAcousticsBlood flowMedicine

Abstract

fetched live from OpenAlex

Mixing is a critical unit operation, which is widely used in chemical and allied industries. Mixing of non-Newtonian fluids is a challenging task due to the complex rheology exhibited by these fluids. Pseudoplastic fluids with yield stress are an important class of non-Newtonian fluids. In this study, we utilized ultrasonic Doppler velocimetry (UDV) to explore the flow field generated by different impellers in the agitation of xanthan gum solutions and pulp suspensions, which are yield-pseudoplastic fluids.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.224
Teacher spread0.205 · 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