MétaCan
Menu
Back to cohort
Record W2331723076 · doi:10.1515/jmsp-2014-0051

Magnetic Damping of Liquid Steel Flows in Horizontal Single Belt Casting (HSBC)

2015· article· en· W2331723076 on OpenAlexaffabout
M. Mahdi Aboutalebi, Mihaiela Isac, R. I. L. Guthrie

Bibliographic record

VenueJournal for Manufacturing Science and Production · 2015
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsNozzleMagnetic fieldTurbulenceMechanicsFluentMaterials scienceLiquid metalFlow (mathematics)Work (physics)Rotating magnetic fieldCastingBrakeMechanical engineeringComputational fluid dynamicsEngineeringPhysicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract A preliminary computational fluid flow model has been developed to simulate the magnetic braking of liquid steel on a water-cooled, rapidly moving, horizontal belt. The liquid steel issuing from the proposed vertical slot-nozzle should ideally move isokinetically with the belt during freezing. In this study, ANSYS Fluent 14.5 software was used to model the 3-D turbulent flow of liquid steel. A 288 core High Performance Computer cluster located at the McGill Metals Processing Centre was used for high-speed computation. The standard k–ε model was used to simulate the turbulence. Similarly, the magnetic induction method was used to calculate the induced heterogeneous magnetic field, from which the current density and electromagnetic forces produced were computed. The behavior of the proposed magnetic flow control was first validated against previous experimental work and was then applied to predict the performance of the proposed slot nozzle. The predicted results show that by applying a DC Magnetic brake to the proposed metal delivery system, near isokinetic conditions can be rapidly established.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.246
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal for Manufacturing Science and ProductionSame topicMetallurgical Processes and ThermodynamicsFrench-language works237,207