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Record W2996067713 · doi:10.5539/jmsr.v9n1p22

Study of Martensitic Transformation in 304L Austenitic Stainless Steel after Tensile and Low Cycle Fatigue Tests

2019· article· en· W2996067713 on OpenAlexvenueno aff
Gláucio Soares da Fonseca, Silvana Carreiro de Oliveira, Jéssica Gadêlha Chaves, PEDRO PENA LEITE, Fabiane Roberta Freitas da Silva, Luiz Carlos Rolim Lopes

Bibliographic record

VenueJournal of Materials Science Research · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsnot available
FundersFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMaterials scienceAusteniteElectron backscatter diffractionMartensiteMetallurgyDiffusionless transformationDeformation (meteorology)MicrostructurePlasticityVolume fractionUltimate tensile strengthTensile testingComposite material

Abstract

fetched live from OpenAlex

There are many studies on austenitic stainless steels with transformation induced plasticity (TRIP). Basically, in these steels, there is a significant increase in strength and toughness with the transformation of austenite to martensite. 304L steel finds extensive application in industry. Studies relating to martensitic transformation with plastic deformation are quite common. Many studies involve monotonic loading relating to the martensite formed. In practice, 304L steels are subject to distinct types of loading and possibly with stress concentrators. Thus, also in smaller quantities, it is possible to find in the literature studies involving cyclic loading with the TRIP effect. To contribute to the literature on the analysis of the TRIP effect on these steels, 304L steel samples with stress concentrators underwent interrupted monotonic tensile tests. Optical microscopy (OM) and x-ray diffraction (XRD) technique characterized the martensitic transformation. Other 304L steel samples with a stress concentrator underwent a low cycle fatigue test. The martensitic transformation, in this case, was possible to follow with the electron backscatter diffraction technique (EBSD). The samples after the interrupted monotonic tests show a high martensite volume fraction formed 1mm away from the notch (30% to 50%), due to the plastic deformation suffered. From 5.5mm of the notch, the samples again display a microstructure like that of the as-received (AR) sample. For the low cycle fatigue tested sample, the high concentration of deformation-induced martensite was within 15mm of the discontinuity. Approximately 0.5mm from the circular discontinuity, the sample again has a microstructure like the initial sample (IS).

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)0.003
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 score0.066
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.036
GPT teacher head0.313
Teacher spread0.278 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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