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Softening Mechanisms of the AISI 410 Martensitic Stainless Steel Under Hot Torsion Simulation

2017· article· en· W2574816874 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMaterials Research · 2017
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do MaranhãoConselho Nacional de Desenvolvimento Científico e TecnológicoMcGill University
KeywordsMaterials scienceSofteningStrain rateIsothermal processMetallurgyMartensiteMicrostructureDynamic recrystallizationToughnessTorsion (gastropod)AusteniteCarbideComposite materialThermodynamicsHot working

Abstract

fetched live from OpenAlex

This study investigated the softening mechanisms of the AISI 410 martensitic stainless steel during torsion simulation under isothermal continuous in the temperature range of 900 to 1150 °C and strain rates of 0.1 to 5.0s-1. In the first part of the curves, before the peak, the results show that the critical (εc) and peak (εp) strains are elevated for higher strain rate and lower temperatures contributing for higher strain hardening rate (h). Moreover, this indicated that dynamic recrystallization (DRX) and dynamic recovery (DRV) are not effective in this region. After the peak, the reductions in stresses are associated to the different DRX/DRV competitions. For lower temperatures and higher strain rates there is a delay in the DRX while the DRV is acting predominantly (with low Avrami exponent (n) and high t0.5). The steady state was reached after large strains showing DRX grains, formation of retained austenite and the presence of chromium carbide (Cr23C6) and ferrite δ at the martensitic grain boundaries. These contribute for impairing the toughness and ductility on the material. The constitutive equations at the peak strain indicated changes in the deformation mechanism, with variable strain rate sensitivity (m), which affected the final microstructure.

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)0.001
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 score0.005
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.088
GPT teacher head0.349
Teacher spread0.261 · 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