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Record W2088899241 · doi:10.1080/10407782.2013.779476

Heat Transfer and Airflow Analysis in the Upper Part of Electrolytic Cells Based on CFD

2013· article· en· W2088899241 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNumerical Heat Transfer Part A Applications · 2013
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsAlcoa (Canada)Natural Sciences and Engineering Research CouncilUniversité Laval
Fundersnot available
KeywordsHeat transfer coefficientAirflowHeat transferComputational fluid dynamicsPressure dropForced convectionNatural convectionMechanicsMaterials scienceThermodynamicsMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A CFD model of the top part of an electrolytic cell used in the primary aluminum industry is presented. The model is used to determine average heat transfer coefficients on the main surfaces, under different ventilation rates. Correlations have been developed for the heat transfer coefficient and pressure drop versus pot draft condition. Nonuniformity of the heat transfer coefficient is studied. Finally, the relative importance of natural convection versus forced convection is revealed by the analysis. The knowledge developed in this article is useful for the heat transfer design and analysis of electrolytic cells, which is crucial in this industry.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.011
GPT teacher head0.233
Teacher spread0.221 · 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