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Record W4300910055

A Two-zone thermal model for predicting the effects of heat transfer on the variation of ice crystal size distribution in slurries

2007· preprint· en· W4300910055 on OpenAlexaff
Masahiro Kawaji, E. Stamatiou, Laurence Fournaison, J. Guilpart

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2007
Typepreprint
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSlurryHeat transferVariation (astronomy)Ice crystalsDistribution (mathematics)ThermalMaterials scienceThermal transferThermodynamicsCrystal (programming language)MechanicsMeteorologyComputer scienceMathematicsPhysicsComposite material
DOInot available

Abstract

fetched live from OpenAlex

A two-zone thermal model has been developed to predict the effects of heat transfer on the size distribution of ice crystals in ice slurries under stagnant conditions. The model extends the homogeneous model recently developed by taking into account the stratification of ice crystals due to gravity. Under adiabatic conditions, the crystal sizes slowly grow due to Oswald ripening, but when heat is externally applied and the ice crystals melt and diminish in size, smaller crystals tend to float to the top of the cell and separated zones of clear liquid and an ice slurry mixture emerge. The temperatures in the two zones diverge as the temperature of the liquid zone rises while that of the ice slurry zone remains constant due to phase change. Measurements of ice crystal size distributions were obtained using direct video observation of the ice slurry crystal behaviour in a stagnant flow cell. For the heating cases, the time to melt all the crystals was sufficiently short (

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)0.005
metaresearch head score (Gemma)0.002
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 score0.481
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
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 science0.0010.000
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 head0.248
Teacher spread0.229 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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