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Record W2562491602 · doi:10.4236/msa.2016.712062

Thermomechanical Behavior Modeling of a Cr-Ni-Mo-Mn-N Austenitic Stainless Steel

2016· article· en· W2562491602 on OpenAlex
Rafael Pereira Ferreira, Eden S. Silva, Carmem Célia Francisco do Nascimento, Samuel Filgueiras Rodrigues, Clodualdo Aranas, Valdemar Silva Leal, Gedeon Silva Reis

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

VenueMaterials Sciences and Applications · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
FundersUniversidade Federal do MaranhãoFundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do MaranhãoConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMaterials scienceSofteningDynamic recrystallizationStacking-fault energyThermodynamicsAusteniteWork hardeningActivation energyMetallurgyHardening (computing)Deformation (meteorology)Austenitic stainless steelKineticsComposite materialDislocationHot workingMicrostructurePhysical chemistryCorrosion

Abstract

fetched live from OpenAlex

The analytical approach and the thermomechanical behavior of a Cr-Ni-Mo-Mn-N austenitic stainless steel were characterized based on the parameters of work hardening (h), dynamic recovery (r) and dynamic recrystallization (n, t0.5), considering constitutive equations (σ, ε) and deformation conditions expressed according to the Zener-Hollomon parameter (Z). The results indicated that the curves were affected by the deformation conditions and that the stress levels increased with Z under high work hardening rates. The σc/σp ratio was relatively high in the first part of the curves, indicating that softening was promoted by intense dynamic recovery (DRV). This was corroborated by the high values of r and average stacking fault energy, γsfe = 66.86 mJ/m2, which facilitated the thermally activated mechanisms, increasing the effectiveness of DRV and delaying the onset of dynamic recrystallization (DRX). The second part of the curves indicates that there was a delay in the kinetics of dynamic softening, with a higher value of t0.5 and lower values of the Avrami exponent (n) due to the competing DRV-DRX mechanisms, and steady state stress (σss) was achieved under higher rates of deformation.

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 score0.033
Threshold uncertainty score0.220

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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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