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Record W4386713306 · doi:10.3390/engproc2023043009

Tensile Properties of the Subsurface and Center Regions of AA6111 Direct-Chill-Cast Ingot in Semisolid State and Their Hot Tearing Susceptibility

2023· article· en· W4386713306 on OpenAlexafffund
Mohamed Qassem, Mousa Javidani, Daniel Larouche, X.-Grant Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversité LavalUniversité du Québec à Chicoutimi
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsIngotMaterials scienceTearingMetallurgyUltimate tensile strengthFormabilityCastingDuctility (Earth science)Composite materialCreepAlloy

Abstract

fetched live from OpenAlex

AA6111 alloys are widely used in the automotive industry owing to their high strength/weight ratio, good corrosion resistance, and reasonable formability. During their manufacture through ingot metallurgy via direct chill (DC) casting, the alloys often suffer from hot tearing, limiting DC casting productivity. The present study focused on evaluating the mechanical properties in the semisolid state and the hot tearing susceptibility of AA6111 DC-cast ingot in the subsurface and center regions. The mechanical behavior of two different regions at high temperatures above solidus was studied using smoothed and notched samples. Tensile tests were performed using the Gleeble 3800 thermomechanical testing unit, and the digital image correlation method was applied to measure the strain evolution. The change in the grain structure in the subsurface and the presence of a high-volume fraction of needle-like β-Fe intermetallics significantly reduced the ductility of the cast ingot in the subsurface region. The hot tearing susceptibility in the subsurface region of the cast ingot was higher than that in the center region. The notch effect is more significant in the subsurface on the stress sensitivity in the presence of stress raisers compared with that in the center region.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.183
Teacher spread0.168 · 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 designBench or experimental
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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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Same topicAluminum Alloy Microstructure PropertiesFrench-language works237,207