MétaCan
Menu
Back to cohort
Record W4404877249 · doi:10.1016/j.jmrt.2024.11.266

High temperature deformation of austenite: Texture and anisotropy effects

2024· article· en· W4404877249 on OpenAlexafffund
Warren J. Poole, Ali Khajezade, Raymond E. Birch, Swagata Roy, Ming‐Lang Tseng, Ashish Dhole

Bibliographic record

VenueJournal of Materials Research and Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of British Columbia
FundersLos Alamos National LaboratoryBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsMaterials scienceAusteniteAnisotropyTexture (cosmology)Deformation (meteorology)MetallurgyCondensed matter physicsComposite materialMicrostructureOpticsArtificial intelligenceImage (mathematics)

Abstract

fetched live from OpenAlex

The deformation of low carbon steels at high temperature in austenite is technologically important but its study is complicated by the decomposition of austenite upon cooling which does not allow for direct characterization of the microstructure. In this study, the grain size and crystallographic texture of austenite were assessed by reconstruction of the prior austenite grains from the ambient temperature bainite. The austenite microstructure was found to consist of nearly equiaxed grains with annealing twins and a texture similar to copper deformed in plane strain. This texture was rationalized by visco-plastic self-consistent (VPSC) simulations. The presence of a non-random texture was predicted to lead to an anisotropic plastic response which was confirmed by experiments. A constitutive model for the high temperature flow stress was established in the Kocks-Mecking framework for work hardening and fit to experiments. The model described the experiments well and was validated by independent compression tests. Finally, the work hardening behaviour was assessed in comparison to other FCC metals. Its behaviour was found to fall between copper and silver, closer to copper.

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 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 score0.009
Threshold uncertainty score0.200

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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 teacher head, 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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Materials Research and TechnologySame topicMicrostructure and Mechanical Properties of SteelsFrench-language works237,207