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Enhanced Ladle Shroud Performance using a Novel Design Concept versus a Conventional Shroud Design

2025· article· en· W4413209704 on OpenAlexafffund
D. R. Gonzalez-Morales, Mihaiela Isac, R. I. L. Guthrie

Bibliographic record

VenueISIJ International · 2025
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
FundersCentre québécois de recherche et de développement de l’aluminiumNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsShroudLadleMaterials scienceMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The Ladle Shroud is an important device in Steelmaking, which aims to protect the deoxidized molten steel from re-oxidation by the atmosphere, prior to casting and solidification. A problem with current designs of ladle shrouds is the negative pressure developed at the upper joint connecting the top of the ladle shroud to the lower nozzle of the ladle. Possible air infiltration makes it essential to protect the said joint with argon shrouding, which in turn leads to a multiphase flow, and the likelihood of forming uncontrolled numbers of large argon gas bubbles. On exiting the ladle shroud, these argon bubbles de-couple from the liquid steel to form TOE’s (“Tundish Open Eyes”) within the overlaying slag layer protecting the steel from the atmosphere. Another problem is the turbulent, multi-phase, flow that is generated during start-up procedures. These can heavily re-oxidize the initial flows of liquid steel. Mathematical and physical water modelling are used in the present work, to propose and study a new Ladle Shroud design. The purpose of the new design is to avoid the negative pressure at the ladle shroud upper joint, to suppress the initial multiphase turbulent flow and to thereby generate microbubbles for the advanced cleaning of liquid steels. The performance of the newly converging-diverging design is compared with a standard reverse taper design. The simulations and experimental results comparing fluid flows between the two designs provide initial proof that the new design will bring improvements to ladle shroud performance.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
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 head0.046
GPT teacher head0.279
Teacher spread0.233 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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