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Fatigue behaviour and life predictions of case‐hardened steels

2009· article· en· W2036392443 on OpenAlexfundno aff
Fengjie Yin, Ali Fatemi

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2009
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsMaterials scienceFractographyNucleationFatigue limitHardened steelResidual stressFracture (geology)Fracture mechanicsCrackingRelaxation (psychology)Crack closureComposite materialStructural engineeringMetallurgyEngineeringThermodynamics

Abstract

fetched live from OpenAlex

ABSTRACT This paper presents experimental and analytical results on fatigue behaviour of case‐hardened steel. Fully reversed strain‐controlled constant amplitude axial fatigue tests were performed on through‐hardened case, through‐hardened core and case‐hardened steel specimens. Surface versus sub‐surface cracking and the role of residual stresses and their relaxation are discussed. Multi‐layer models of the case‐hardened specimens were used to predict crack nucleation sites as well as fatigue lives, and the predictions corresponded well with the experimental results. Linear elastic fracture mechanics (LEFM) was also used to conduct fatigue crack growth analysis to further explain the experimental observations from the fracture surfaces of the case‐hardened specimens. A fatigue strength estimation method based on hardness and inclusion size was used to estimate the fatigue limit of the materials investigated. Fractography of fracture surfaces and crack nucleation location are also presented.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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

Citations21
Published2009
Admission routes1
Has abstractyes

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