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Progress in Strip Casting Technologies for Steel; Technical Developments

2013· article· en· W2091108535 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

VenueISIJ International · 2013
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsCastingEngineeringNear net shapeProcess (computing)Continuous castingManufacturing engineeringMechanical engineeringSand castingMetallurgyMoldMaterials scienceComputer scienceComposite material

Abstract

fetched live from OpenAlex

The present article is a sequel to the previous review on the history of near net shape strip casting facilities. The present review focuses on technical progress made in strip casting over the last three decades. Strip casting is a revolutionary technology that promises the hope for an efficient, economical and environmentally-friendly process to produce hot-rolled, steel sheets. This review provides a summary of the theory, recent research, and progress, in the developments of strip casting operations for steels, along with technical discussions regarding the characteristics and design features of steel strip casting machines. Two strip casting processes are discussed in detail; the Twin-Roll Casting (TRC) process and the Horizontal Single-Belt Casting (HSBC) process. Particular emphasis is placed on topics such as the commercial potential for strip casting technology in the steel industry, and the economic and environmental advantages of direct strip production, versus current continuous casting, fixed mold technologies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.288

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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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