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Record W2537490063 · doi:10.1111/ffe.12514

2D modelling of inclined intergranular stress corrosion crack paths

2016· article· en· W2537490063 on OpenAlexaboutno aff
J. Griggs, Erwin Gamboa, Olivier Lavigne

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsnot available
FundersAustralian Government
KeywordsIntergranular corrosionMaterials scienceStress corrosion crackingCrackingMetallurgyComposite materialElectrochemistryCorrosionStrain (injury)Inclination angleStress (linguistics)Crack closureFracture mechanicsStructural engineeringElectrode

Abstract

fetched live from OpenAlex

Abstract Inclined high pH stress corrosion cracking (SCC) is a type of intergranular environmental cracking in gas pipelines, which differs from typical SCC by propagating at an angle from the wall direction. Investigations of Australian and Canadian inclined SCC colonies have not provided a clear indicator of a cause for the abnormal crack growth direction. This paper addresses the possibility of crack tip strain enhanced electrochemistry causing the inclination. Potentiodynamic tests were conducted to quantify the influence of strain on the electrochemistry, and strain was found to increase current density up to 300% in the SCC region. A model was developed that incorporates crack tip strain driven SCC growth, which showed good agreement with field grown cracks, and the aspect ratio of the grains was shown to have an effect on the inclination angle. The results indicate that crack tip strain enhanced electrochemistry is a plausible cause for inclined SCC.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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