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Record W4377104061 · doi:10.1080/03019233.2023.2201751

Influence of mould level instability on the unevenness of solidified shell deformations during continuous casting

2023· article· en· W4377104061 on OpenAlexaff
Kohei Furumai, Hatem S. Zurob, A.B. Phillion, Katsunari Oikawa

Bibliographic record

VenueIronmaking & Steelmaking Processes Products and Applications · 2023
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInstabilityMaterials scienceShell (structure)MetallurgyCrackingCastingComposite materialContinuous castingInfiltration (HVAC)Steel castingMicrostructureMechanicsPhysics

Abstract

fetched live from OpenAlex

The influence of mould level instability during continuous casting on the unevenness of the initial solidified shell in hypo-peritectic steels has been investigated.Water model experiments and inplant casting experiments revealed that mould level instability, which increases with increasing casting speed, is related to longitudinal cracking resulting from the unevenness of the solidification shell.A numerical model which considers the effect of mould level instability was developed and used to simulate the formation of the unevenness of the solidification shell and solidified shell deflections.The calculation results show that an increase in the non-uniform infiltration of mould flux increases the unevenness of the solidified shell.On the other hand, the unevenness of the solidified shell decreases due to mild cooling.Overall, the results of the plant tests and calculations show that non-uniform infiltration of mould flux dramatically affects air gap formation and the unevenness of the solidified shell.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 science0.0000.000
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 head0.027
GPT teacher head0.232
Teacher spread0.204 · 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 designObservational
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

Citations10
Published2023
Admission routes1
Has abstractyes

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