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Record W1999464681 · doi:10.1002/aic.11245

Settling of dilute and semidilute fiber suspensions at finite <i>Re</i>

2007· article· en· W1999464681 on OpenAlexafffund
Juha Salmela, D. Mark Martinez, Markku Kataja

Bibliographic record

VenueAIChE Journal · 2007
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSettlingSedimentationVolume fractionSuspension (topology)FiberVolume (thermodynamics)ViscosityMechanicsRefractive indexTRACERMaterials scienceChemistryThermodynamicsOpticsPhysicsMathematicsGeologyComposite materialGeomorphology

Abstract

fetched live from OpenAlex

Abstract The motion of tracer fibers settling in a suspension made optically transparent using an index‐of refraction matching technique is studied as a function of concentration, aspect ratio, fluid viscosity, and fiber length distribution. At Re ∼ O (1), two different regimes of sedimentation are clearly identified. For small volume fractions we find that fibers settle with their long‐axis preferentially in the horizontal state. With increasing volume fraction, fibers settle preferentially with their long‐axis aligned in the direction of gravity. These findings are strikingly different than for those conducted with Re → 0 and qualitatively support the numerical simulations reported by Kuusela et al. © 2007 American Institute of Chemical Engineers AIChE J, 2007

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2007
Admission routes2
Has abstractyes

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