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Record W4391970128 · doi:10.1111/ffe.14261

Full‐scale testing of near‐neutral pH stress corrosion cracking growth behavior of a vintage X52 oil pipe

2024· article· en· W4391970128 on OpenAlexafffund
Haotian Sun, Yan Li, Darren Bibby, Jean‐Philippe Gravel, Jidong Kang, Wenxing Zhou

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2024
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsNatural Resources CanadaWestern University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMetallurgyStress corrosion crackingCorrosionCrackingStress (linguistics)Stress concentrationStress intensity factorGrowth rateBase metalComposite materialFracture mechanicsWelding

Abstract

fetched live from OpenAlex

Abstract This study presents an experimental investigation conducted on a 40‐year‐old vintage X52 oil pipe segment to assess the growth behavior of near‐neutral pH stress corrosion cracking (SCC). Six cracks were introduced on the pipe specimen, each of which was associated with a unique combination of metallurgical and environmental condition. SCC growth was evident in two base metal cracks respectively exposed to C2 and NS4. Stress intensity factors at the two cracks were evaluated using extended finite element method. Near‐neutral pH environment effects were observed to have a more pronounced effect on the stress intensity factor threshold for growth than on the growth rate. Higher stress levels and aging likely contribute to the difference in growth rates of different cracks. Electrochemical analysis suggests the corrosion‐crack propagation interplay, with a faster corrosion in the NS4 solution than that in the C2 solution consistent with the observed slower crack growth in NS4.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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.

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

Citations2
Published2024
Admission routes2
Has abstractyes

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