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Comparison of carbonitriding and nitrocarburising on size and shape distortion of plain carbon SAE 1010 steel

2010· article· en· W1977295214 on OpenAlexaff
Victoria Campagna, Randy J. Bowers, D. O. Northwood, X. Sun, Peter Bäuerle

Bibliographic record

VenueSurface Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCarbonitridingMaterials scienceCarbon steelMetallurgyDistortion (music)Carbon fibersComposite materialCorrosion

Abstract

fetched live from OpenAlex

Carbonitriding is a widely accepted method of heat treatment used by North American manufacturers for plain carbon steel. While the process imparts a hard, wear resistant case, it is also associated with both size and shape distortion, which can be problematic for components in tight fitting assemblies. This research compares the effects of the carbonitriding and nitrocarburising processes on SAE 1010 steel with respect to residual stress and distortion. Results indicate that the two processes develop residual compressive stresses and are associated with both size and shape distortion. Although the magnitude of the compressive stresses in nitrocarburised steels is lower, this process was noted to give rise to overall smaller dimensional changes than the carbonitriding process. The findings from this study are applied to a manufacturing application involving the surface treatment of a thin shelled automotive component in a light loading application.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.215
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 source (direct Gemma or distilled Codex), 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

Citations11
Published2010
Admission routes1
Has abstractyes

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