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Record W2125159395 · doi:10.1002/ceat.201300409

Experiments and Simulations on Bidisperse Solids Suspension in a Mixing Tank

2013· article· en· W2125159395 on OpenAlex
Inci Ayranci, Suzanne M. Kresta, J.J. Derksen

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

VenueChemical Engineering & Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImpellerBaffleSuspension (topology)Lattice Boltzmann methodsTurbulenceMechanicsMixing (physics)Eulerian pathLarge eddy simulationMaterials scienceMechanical engineeringEngineeringPhysicsLagrangianMathematics

Abstract

fetched live from OpenAlex

Abstract Experiments and simulations of a solids suspension process in a lab‐scale stirred tank under turbulent conditions have been performed. Two impellers have been tested. The liquid‐solid suspension consists of water and a mixture of glass and bronze particles. The simulations are Eulerian‐Lagrangian with the liquid flow as the Eulerian part, being solved by means of a lattice‐Boltzmann method combined with a large‐eddy approach to turbulence modeling. Comparison with experimental visualizations indicates that the simulations are able to represent the start‐up of the suspension process from a zero‐velocity initial condition. Differences between experiment and simulation are observed near the bottom of the tank. The simulation data are used to highlight the collisional interaction between the two different types of solids, the role of baffles, and the effect of impeller type on the suspension process.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.676

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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