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Record W2015076168 · doi:10.1021/ie801518p

A Model To Predict the Concentration of Dispersed Solid Particles in an Aqueous Medium Confined inside Horizontal Cylindrical Channels

2009· article· en· W2015076168 on OpenAlexaff
Herbert Loría, Pedro Pereira‐Almao, Carlos E. Scott

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Calgary
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsSuspension (topology)CylinderMechanicsDeposition (geology)Materials scienceAqueous solutionMicrometerConvectionCross section (physics)Range (aeronautics)Particle (ecology)ChemistryOpticsComposite materialGeometryPhysicsGeology

Abstract

fetched live from OpenAlex

The deposition of solid particles in cylindrical channels has received considerable attention, because of its direct application in industry. However, an adequate mathematical expression that studies the separation and suspension of dispersed particles present in horizontal cylindrical channels is still missing. In this paper, we developed and solved a time-dependent, two-dimensional convective-dispersive model that simulates the deposition and suspension of dispersed particles immersed in a fluid medium inside the cross section of a horizontal cylindrical channel in a stagnant situation. The results of the modeling are compared with a series of experiments that permit one to know the concentration of the particles in different points in the cross section of a horizontal cylinder. These experiments were performed using particles in the micrometer range dispersed in an aqueous medium. The conditions that permit to control the suspension and deposition of the particles inside a liquid medium with cylindrical geometry are unveiled by the presented model.

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)0.001
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 score0.217
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.069
GPT teacher head0.314
Teacher spread0.245 · 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

Citations8
Published2009
Admission routes1
Has abstractyes

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