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Influence of Multi-Step Austempering Temperature on Tensile Performance of Unalloyed Ductile Iron

2019· article· en· W2946152754 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKey engineering materials · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAustemperingMaterials scienceUltimate tensile strengthAusteniteMetallurgyElongationFerrite (magnet)Ductility (Earth science)MartensiteDuctile ironQuenching (fluorescence)Isothermal processCast ironComposite materialBainiteMicrostructureCreep

Abstract

fetched live from OpenAlex

Austempered ductile iron (ADI) has been widely used in various industries due to its excellent combination of high strength, ductility and good wear resistance. The tensile behavior of an unalloyed commercial ADI with a multiphase structure designed by a novel multi-step austempering treatment is investigated. The developed austempering process consists of austenitizing at 890°C for 20min, then initial rapid quenching to 180°C, and isothermal holding at 190, 220, 250°Cfor 120min, and finally air cooling to room temperature. The optimum mechanical properties with an ultimate tensile strength of 1350MPa, a yield strength of 1090MPa, as well as an elongation of 3.5% is achieved at 220°C. This is attributed to a synergistic strengthening effect of multiphase structure including a prior martensite with fine needle bainitic ferrite and film retained austenite.

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 score0.370
Threshold uncertainty score0.872

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 head0.005
GPT teacher head0.174
Teacher spread0.169 · 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