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Record W165460789 · doi:10.1002/srin.200506015

Development of Single‐Belt Strip Casting Simulator

2005· article· en· W165460789 on OpenAlexaff
Hiroshi Nogami, Pedro Gutemberg Quariguasi Netto, R. I. L. Guthrie

Bibliographic record

Venuesteel research international · 2005
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsMcGill University
FundersJapan Society for the Promotion of Science
KeywordsCastingBar (unit)Materials scienceMechanical engineeringHeat transferMetallurgyEngineeringComposite materialMechanics

Abstract

fetched live from OpenAlex

Near‐net‐shape casting is one of the key technologies to improve process efficiency of steel production. Single‐belt strip casting is recognized as a promising technology for thin strip production because of the advantages like well‐controlled heat transfer rate, flexibility in production rate, compactness of equipment, and so on. In this study a newly designed simulator of the single‐belt strip casting process was developed. The simulator solidifies molten metal on the running solid metal bar with a groove for molten metal deposition pushed by a pneumatic cylinder. Capability of this simulator design was discussed by one‐dimensional numerical heat transfer analysis. It showed that a steel casting bar thicker than 40 mm was capable of casting test of 10 mm thick steel strip even if interfacial thermal resistance existed. Finally, the simulator was applied to the casting test of aluminum strip, and successfully estimated the variation of the interfacial heat flux from the solidifying strip to the casting bar.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.001

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 head0.095
GPT teacher head0.337
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2005
Admission routes1
Has abstractyes

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