MétaCan
Menu
Back to cohort
Record W1989888383 · doi:10.1002/aic.13889

Highly resolved simulations of solids suspension in a small mixing tank

2012· article· en· W1989888383 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.

Bibliographic record

VenueAIChE Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSuspension (topology)ImpellerMechanicsLattice Boltzmann methodsTurbulenceBaffleFlow (mathematics)DispersityAgitatorMixing (physics)Reynolds numberMaterials sciencePhysicsThermodynamicsChemical engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

Abstract Simulations of solid–liquid flow in an agitated tank have been performed. The simulations fully resolve the mildly turbulent liquid flow (Re ≈ 2000) in the tank, and the spherical solid particles suspended in the liquid. Full resolution of the particles sets the grid spacing and thereby limits the tank size and the number of particles (up to 3600 in this article) that are computationally affordable. The solids volume fraction is some 8%. The lattice‐Boltzmann method has been used to solve the flow dynamics; the particles move under the influence of resolved hydrodynamic forces, unresolved lubrication forces, net gravity, and collisions (with other particles, the tank wall, and the impeller). We show the start‐up of the suspension process, demonstrate its dependency on a Shields number (that we interpret in terms of the Zwietering correlation) and show the impact of polydispersity on the suspension process. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3266–3278, 2012

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.408

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 head0.037
GPT teacher head0.272
Teacher spread0.234 · 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