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Record W1979578207 · doi:10.1179/174328109x445732

Optimisation of dual purging location for better mixing in ladle: a water model study

2009· article· en· W1979578207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIronmaking & Steelmaking Processes Products and Applications · 2009
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsMixing (physics)LadleArgonTRACERVolumetric flow rateMechanicsPorosityFlow (mathematics)Dual purposeMaterials scienceChemistryMetallurgyMechanical engineeringComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Mixing time studies were performed on a one-fifth scale aqueous model of a single tapered ladle with different bottom purging locations. Two porous plugs were used simultaneously to purge compressed air as an analogue to argon and this was referred as dual purging. KCl solution (1 N) was used as the tracer for measuring mixing time. The scaled down gas flowrate varied from 10 to 80 L m–1. Around 400 experiments were done including all possible dual purging locations and the location which gives least mixing time was identified. The results were compared with corresponding single purging experiments and it was found that dual purging can reduce mixing time to a great extent even in the lower flowrate range and a location better than ±R/2 has been suggested. Effect of differential flow on mixing time has also been reported.

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.

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 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: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.670

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)0.0000.000

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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