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Record W2340473926 · doi:10.5006/2045

Stress Enhanced Corrosion at the Tip of Near-Neutral pH Stress Corrosion Cracks on Pipelines

2016· article· en· W2340473926 on OpenAlexaff
Yao Yang, Y. Frank Cheng

Bibliographic record

VenueCORROSION · 2016
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCorrosionMaterials scienceStress (linguistics)Pipeline transportMetallurgyStress corrosion crackingComposite materialChemistry

Abstract

fetched live from OpenAlex

In this work, corrosion at the tip of stress corrosion cracks on an X65 pipeline steel was investigated under various stress levels in a near-neutral pH solution. Electrochemical and micro-electrochemical measurements, combined with surface characterization and stress simulation, were conducted to understand the mechanistic aspects of stress enhanced corrosion at crack tip and its role in crack propagation in the steel. Results demonstrated that significant stress concentrations can develop at crack tip and enhance corrosion of the steel in the solution. The steel is in an active dissolution state. The crack propagation rate increases with the enhanced corrosion at the crack tip. However, the cracking mechanism is stress dependent. At the applied load of 600 N, the crack propagation is mainly a result of the steel dissolution at the crack tip. When the local stress level at the crack tip is smaller than this value, corrosion, rather than cracking, occurs inside the crack. When the stress level at the crack tip is sufficiently high to exceed the stress associated with the applied load of 600 N, corrosion becomes less important in the cracking process. Instead, the stress factor dominates the stress corrosion crack propagation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 designObservational
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

Citations28
Published2016
Admission routes1
Has abstractyes

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Same venueCORROSIONSame topicHydrogen embrittlement and corrosion behaviors in metalsFrench-language works237,207