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Record W2800025355 · doi:10.1139/tcsme-2000-0011

MODELING OF CONCENTRATED SUSPENSION FLOW

2000· article· en· W2800025355 on OpenAlexafffundvenue
Jiangyou Long, P. Chen

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuspension (topology)MechanicsFlow (mathematics)Newtonian fluidMaterials scienceRheologyNon-Newtonian fluidPhysicsComposite materialMathematics

Abstract

fetched live from OpenAlex

The volume-and-time averaged model for mono-disperse suspension flow developed by Liu [1] has been applied to simulate the flow behaviors of concentrated suspensions through circular/rectangular conduits, and it has further extended to bi-disperse suspensions. The suspensions in this study are composed of non-colloidal, rigid, mono-/bi-sized, spherical particles and viscous Newtonian fluids, and undergo pressure-driven flow. For the mono-disperse system, the model is successful in simulating the velocity and concentration profiles of fully developed suspension flow through circular tubes and rectangular channels. For the bidisperse system, the velocity profiles of suspensions and the concentration profiles of two species of particles for fully developed flow through rectangular channels are obtained. To our knowledge this paper provides the first approach to simulate the pressure-driven flow of a bi-disperse system. All the simulated profiles of this study agree well with the literature data, and no adjustable parameter was used in the simulations.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.419

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 head0.015
GPT teacher head0.205
Teacher spread0.191 · 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

Citations0
Published2000
Admission routes3
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicLattice Boltzmann Simulation StudiesFrench-language works237,207