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Record W7019339293

Experimental simulation of dross generation for GA and GI operations

2011· article· en· W7019339293 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2011
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsnot available
FundersArcelorMittal
KeywordsDrossZincVolumetric flow rateCrucible (geodemography)InjectorFlow (mathematics)Rotational speedGraphite
DOInot available

Abstract

fetched live from OpenAlex

A bench scale simulation of skimmings generation was conducted in this study as well as an analysis into the rates of skimmings generation at the industrial level. The experimental apparatus consists of a graphite crucible containing liquid zinc at 460°C which is stirred using a six bladed impeller. A jet of either nitrogen or air was directed on to the bath liquid surface simulating the flow from the air knives. The rate of skimmings generated for variable rotational speeds was measured for zinc compositions corresponding to GA and GI operations. Moreover, a numerical simulation of liquid zinc flow in the crucible was carried out to determine the surface area of the liquid zinc free surface exposed to the gas stream. This calculation was used to determine the rate of skimmings generated per unit surface area for each rotational speed. It was found that the rate of skimmings generated increased with surface velocity and the rate using nitrogen was lower than for air. Furthermore, dross particles imbedded in the skimmings from both laboratory and industrial samples were similar in morphology and composition.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.260
Teacher spread0.214 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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