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Record W3048605974 · doi:10.1063/5.0019021

Dean flow velocity of viscoelastic fluids in curved microchannels

2020· article· en· W3048605974 on OpenAlex
Arsalan Nikdoost, Pouya Rezai

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

VenueAIP Advances · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsYork University
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsViscoelasticityDragMechanicsNewtonian fluidMicrofluidicsDisplacement (psychology)ViscosityFlow (mathematics)RADIUSMaterials scienceClassical mechanicsPhysicsNanotechnologyComposite materialComputer science

Abstract

fetched live from OpenAlex

Curved microchannels take advantage of inertial and Dean drag forces to achieve size-based separation of particles and cells. Despite the reported numerical and experimental correlations for Dean velocity (VDe) of Newtonian fluids, comprehensive studies and correlations are still required for the flow of viscoelastic fluids in curved microchannels. In this paper, the effects of curved channel height, radius of curvature, and kinematic viscosity were investigated to derive an empirical correlation for VDe of viscoelastic water. The developed knowledge of viscoelastic Dean flow velocity will be vital in design of elasto-inertial microfluidic devices for determination of lateral displacement of fluids in fluid exchange and Dean drag force in particle focusing and separation 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 score0.108
Threshold uncertainty score0.444

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 head0.013
GPT teacher head0.208
Teacher spread0.196 · 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