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Record W4205121110 · doi:10.1520/jte20210457

Retained Austenite Transformation-Induced Residual Stress Change in Carburized 16MnCr5 Steel

2022· article· en· W4205121110 on OpenAlexaff
Wanhua Liang, James Pineault, F.A. Conle, Timothy H. Topper

Bibliographic record

VenueJournal of Testing and Evaluation · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsPROTO Manufacturing (Canada)University of Waterloo
Fundersnot available
KeywordsAusteniteMaterials scienceResidual stressComposite numberMetallurgyMartensiteFinite element methodComposite materialStructural engineeringMicrostructure

Abstract

fetched live from OpenAlex

ABSTRACT Carburization, a heat treatment commonly used in industries to improve fatigue performance of components, usually results in untransformed austenite in a transformed matrix of martensite or other phases. The subsequent transformation of the retained austenite due to service loading is complex and can result in the alteration of beneficial residual stresses. The amount of retained austenite decomposed under a few axial loading cases was determined by measuring the retained austenite content before and after loading of through-carburized- and carburized case only (composite)–hardened 16MnCr5 steel samples. Separate case and core stress−strain curves and the retained austenite transformation in the case layer of the composite model were used to predict the stress−strain and the residual stress behavior of the composite samples with a simple compatibility model and a finite element model.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.294

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 studies0.0000.000
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 head0.083
GPT teacher head0.281
Teacher spread0.198 · 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 designSimulation or modeling
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

Citations0
Published2022
Admission routes1
Has abstractyes

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