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Record W2469599212 · doi:10.1002/cjce.22591

A submodel for spherical particles undergoing phase change under the influence of convection

2016· article· en· W2469599212 on OpenAlexafffundvenue
Hemant Bansal, Petr A. Nikrityuk

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGrashof numberMicroscale chemistryMechanicsHeat transferReynolds numberFlow (mathematics)ThermodynamicsConvectionForced convectionMaterials scienceNusselt numberPhysicsMathematicsTurbulence

Abstract

fetched live from OpenAlex

ABSTRACT This work is devoted to the development and validation of a subgrid model describing heat transfer between the bulk flow and moving particles undergoing phase change under the influence of forced and free convection. Such kinds of submodels play the role of “scale bridges” between microscale (e.g. interfacial heat transfer) and macroscale (e.g. bulk flow) phenomena. Applied to multiscale modelling of particulate flows with phase change phenomena, our model serves as a coupling between equations describing particle movement in Lagrangian space and the mass and heat conservation equation defining melt flow in Eulerian space. The input parameters in our model are the particulate Reynolds number ( Re ), the Grashof number ( Gr ), the Stefan number ( Ste ), and the Prandlt number ( Pr ). The model has been validated against experimental data published recently in the literature applied to the melting of ice spheres under different flow conditions. Good agreement between our model predictions and published experimental data (Shukla et al. [16] and Hao and Tao [14] ) is observed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.209

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 head0.019
GPT teacher head0.212
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

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 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

Citations12
Published2016
Admission routes3
Has abstractyes

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