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Influence of thermal diffusion on decarburisation of iron–chromium alloy droplets by oxygen–argon gas mixtures

2014· article· en· W2079409862 on OpenAlexafffund
Patricia Wu, Yi Yang, Mansoor Barati, Alex McLean

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2014
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDecarburizationAlloyArgonMass transferDiffusionChromiumOxygenMetallurgyMaterials scienceThermodynamicsRefining (metallurgy)Chemistry

Abstract

fetched live from OpenAlex

Using an electromagnetic levitation technique, the kinetics of decarburization of Fe-Cr-C alloy droplets by oxygen-argon gas mixtures containing up to 10% oxygen was investigated at 1873K. Conventional formulation of governing mass transport numbers did not describe the experimental observations made during this study. It is hypothesized that the effects of thermal diffusion caused by the steep temperature gradient (~1550 degrees) between the incoming gas stream and the surface of the droplet, is responsible for the offset observed between the well-established mass transfer model and the experimental data for decarburization kinetics. This finding has important implications with respect to the application of appropriate mass/heat transport equations when using commercial software to model pyro-metallurgical processes, such as stainless steel refining, where large temperature gradients are an inherent component of the system.

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 categoriesMeta-epidemiology (narrow)
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 score0.520
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)0.0000.000

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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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 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

Citations2
Published2014
Admission routes2
Has abstractyes

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