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Record W2043425482 · doi:10.1115/imece2013-63801

Stratification in Isothermal Ice-Slurry Pipe Flow

2013· article· en· W2043425482 on OpenAlexaff
Charles Landa Onokoko, Nicolas Galanis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsLaminar flowBuoyancyMechanicsSlurryTurbulenceInletIsothermal processMaterials scienceStratification (seeds)Boundary layerGeologyThermodynamicsPhysicsComposite materialGeomorphology

Abstract

fetched live from OpenAlex

A single-phase 3D model for isothermal laminar and turbulent flow of an ice slurry in a horizontal pipe is used to investigate the effects of the uniform inlet velocity and ice concentration on their axial evolution. The slurry is modeled as a Newtonian fluid with effective local properties depending on the local ice concentration. Despite the relative simplicity of this model (compared to the two-phase models used elsewhere) its numerical solution gives results which correctly reflect experimental observations. Specifically, these results show that as the fluid moves downstream the ice concentration increases in the upper part of the pipe and it decreases in the lower part. The velocity profile is principally influenced by the boundary layer growth close to the inlet but further downstream it becomes asymmetrical with respect to the horizontal symmetry plane with higher velocities in the lower part of the pipe. The differences between the values in the upper and lower parts of the pipe are much more important in the case of laminar flow. The results are analyzed by considering the phenomena influencing the ice particle movement (buoyancy and diffusion) and the relation between ice concentration and the thermophysical properties of the slurry.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

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)0.0050.001

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations4
Published2013
Admission routes1
Has abstractyes

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