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Record W4308576172 · doi:10.3390/met12111906

Influence of Hot Top Height on Macrosegregation and Material Yield in a Large-Size Cast Steel Ingot Using Modeling and Experimental Validation

2022· article· en· W4308576172 on OpenAlex
Neda Ghodrati, Mounir Baiteche, Abdelhalim Loucif, Paloma Isabel Gallego, Jean-Benoît Morin, Mohammad Jahazi

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSolidification and crystal growth phenomena
Canadian institutionsCégep de Sorel-TracyÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIngotLiquidusMaterials scienceMetallurgyShrinkageYield (engineering)Continuous castingFlow (mathematics)AlloyMechanicsComposite material

Abstract

fetched live from OpenAlex

The effect of the hot top height on the formation of positive and negative macrosegregation patterns, the ingot quality, and the material yield during solidification of a 12 MT cast ingot made of a Cr-Mo-low alloy steel was investigated. A 3D numerical simulation of the process was conducted using finite element modeling. A full-size 12 MT ingot was cut off from its center in the longitudinal direction, and a large cross-section was sliced into small samples. The chemical mapping of all the elements in the steel composition was obtained for all samples and compared with the model predictions for validation purposes. The influence of the increase in hot top height on the liquid metal velocity field, size and shape of vortexes, cooling rate of the liquid, and liquidus temperature was determined. Results revealed that increasing the hot top height by 165 mm increased the solidification time, fluid velocity in regions including the hot top and ingot bottom, and decreased the local liquidus temperature. The combination of all the above resulted in an overall decrease in positive and negative macrosegregation of more than 6% and an increase in ingot quality. The results are interpreted based on the interactions between the transport of solute and heat coupled with the flow driven by thermo-solutal convection and shrinkage-induced flow.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.349

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 head0.038
GPT teacher head0.284
Teacher spread0.247 · 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