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Record W2299810951

Modeling of Continuous Electromagnetic Removal of Inclusions from Molten Metals

2009· article· en· W2299810951 on OpenAlexaff
M.R. Aboutalebi, M. Isac, Guthrie R.I.L.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2009
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMolten metalMetallurgyInclusion (mineral)Materials scienceChemistryMineralogy
DOInot available

Abstract

fetched live from OpenAlex

In this research, a 3-D mathematical model is developed for simulating electromagnetic continuous removal of inclusions from molten metals. The model includes the computation of electromagnetic force field and fluid flow in the presence of electromagnetic forces. The results of flow field together with electromagnetic force field were further used for calculating the trajectory of inclusions in the molten metal. Parametric studies were performed to evaluate the effects of various parameters such as magnetic field intensity, inclusion size, and fluid velocity on inclusion removal efficiency in molten magnesium. In order to verify the mathematical model and visualize the trajectories of particles in the melt flow under electromagnetic force, a physical model was constructed. The predicted particle trajectories and separation in the physical model were compared with those obtained from experiments, which showed a relatively good agreement.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.103
GPT teacher head0.450
Teacher spread0.347 · 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
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

Citations0
Published2009
Admission routes1
Has abstractyes

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