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Initiation of Dynamic Recrystallization in Constant Strain Rate Hot Deformation

2003· article· en· W2075383544 on OpenAlexaff
Evgueni I. Poliak, J. J. Jonas

Bibliographic record

VenueISIJ International · 2003
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMcGill University
Fundersnot available
KeywordsDynamic recrystallizationMaterials scienceStrain rateFlow stressAusteniteStrain hardening exponentMetallographyConstant (computer programming)Deformation (meteorology)Stress (linguistics)MetallurgyComposite materialThermodynamicsHot workingMicrostructurePhysics

Abstract

fetched live from OpenAlex

In constant strain rate tests, the occurrence of dynamic recrystallization (DRX) is traditionally identified from the presence of stress peaks in flow curves. However, not all materials display well-defined peaks when tested under these conditions. Using plain carbon, Nb-bearing and 321 austenitic stainless steels, it is shown that the onset of DRX can also be detected from inflections in plots of the strain hardening rate θ against stress σ or, equivalently, from inflections in ln θ-ln σ and ln θ-ε plots regardless the presence of stress peaks in the flow curves. These observations are verified by means of metallography. A unified description of the flow curve is introduced based on normalization of the stress and strain by the respective peak or steady state values. This approach reveals that, in a given material, the ratio of DRX critical stress to the peak or steady state stress is constant, as is that of the critical strain to the corresponding strain values. Furthermore, it is shown that the present technique can be used to establish the occurrence of DRX when this cannot be determined unambiguously from the shape of the flow curve.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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".

Quick stats

Citations460
Published2003
Admission routes1
Has abstractyes

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