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Retained Austenite - Residual Stress - Distortion Relationships in Carburized SAE 6820 Steel

2007· article· en· W2034887848 on OpenAlexaff
Derek O. Northwood, Lily He, Erin C. Boyle, Randy J. Bowers

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAusteniteCarburizingResidual stressMaterials scienceTemperingMetallurgyQuenching (fluorescence)MicrostructureComposite material

Abstract

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SAE 8620 steel is typically used in the carburized condition for powertrain applications in the automotive industry, e.g. gears, roller bearings, camshafts. Such steels always contain retained austenite to varying degrees in the as-hardened and also in the tempered microstructures. As well as retained austenite, heat treatment can produce residual stresses, which lead to distortion (size and shape). The intent of this study was to investigate the effect of heat treatment parameters on the amount of retained austenite, residual stress and distortion in carburized SAE 8620 steel. A specially designed specimen, the Navy C-ring, was used for this study. The steel was first normalized prior to machining the Navy C-ring specimens. The specimens were then heat treated by carburizing at 927°C or 954°C (1700°F or 1750°F) at four levels of carbon potential (0.9, 1.0, 1.1, 1.2) followed by oil quenching and tempering at either 149°C or 177°C (300°F or 350°F). The distortion of the C-ring was evaluated by dimensional measurements of the inner diameter, outer diameter, gap width and thickness for size distortion, as well as flatness, cylindricity and roundness for shape distortion. X-ray diffraction (XRD) techniques were used to determine the residual stress and the amount of retained austenite. The amount of retained austenite was also measured by optical metallography. The amount of retained austenite and the residual stress increased with increasing carburizing temperature and carbon potential and decreased upon tempering. There was not a significant further reduction in the amount of retained austenite and residual stress when the tempering temperature was increased from 149°C to 177°C. Distortion was influenced by both the amount of retained austenite and the magnitude of the residual stress. With increasing retained austenite/residual stress, the distortion became more serious. Based on the distortion data for 3 parameters (OD, gap width and flatness) for the quenched and tempered specimens, the amount of retained austenite for minimum distortion was approximately 25%.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.521

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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

Citations6
Published2007
Admission routes1
Has abstractyes

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