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Record W2004062503 · doi:10.1615/ichmt.2012.cht-12.470

COMPLEX HEAT TRANSFER AT DIRECTED CRYSTALLIZATION OF SEMITRANSPARENT MATERIALS

2012· article· en· W2004062503 on OpenAlexaff
Iurii Lokhmanets, Valeriі Deshko, Аnton Karvatskii

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsHeat transferCrystallizationMaterials scienceThermal radiationConvectionConvective heat transferMechanicsCrystal growthCrystal (programming language)OpticsThermodynamicsPhysicsComputer science

Abstract

fetched live from OpenAlex

The sensibility of thermal regimes at crystal-melt system to inner or outer parameters was studied for semitransparent media by the numerical simulation of complex heat transfer. A model of radiation-convective and radiation-conductive heat transfer was developed. Advanced features of the model, such as dynamic evolution of interface, were realized by implementation of user-defined functions. The 2D axisymmetric model is limited geometrically to the cylindrical crystal-melt system since heat regimes and temperature gradients in the area near crystallization front are the most important. Combined effect of radiation, convective and conductive heat transfer mechanisms on the formation of temperature fields and heat flows, position and shape of the crystallization front and distribution of the temperature gradients in the crystal-melt system have been examined for the oxide and alkali-halide classes of semitransparent materials at different growth conditions, considering selectivity of their absorption. Analysis of the results allowed developing the recommendations for approximation of the effects of radiation and convection heat transfer and their interaction. This allows justification of several possible simplifying approaches at development of the numerical models of crystal growth furnaces, including on-line models for operative control of the growth 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.

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 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 score0.115
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)0.0010.000

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 head0.031
GPT teacher head0.234
Teacher spread0.203 · 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.

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
Published2012
Admission routes1
Has abstractyes

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