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Record W70399822 · doi:10.5006/c2008-08500

The Influence of Weld Heat-Affected Zone on Stress Corrosion Cracking of Pipeline Steel in Near-Neutral PH Environment

2008· article· en· W70399822 on OpenAlexaff
Bin Fang, J. Wang, Wei Ke, R.L. Eadie, M. Elboujdaîni, Wenyue Zheng, Winston Revie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of AlbertaNatural Resources Canada
Fundersnot available
KeywordsStress corrosion crackingWeldingMetallurgyMaterials scienceCorrosionPipeline (software)Stress (linguistics)CrackingComposite materialEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Colonies of stress corrosion cracks are often seen around weld heat-affected zones (HAZs) in pipelines that are operating in the field in contact with near-neutral pH (NNPH) environment. Research on stress corrosion cracking (SCC) of welded line pipe steel can contribute knowledge that is important in establishing pipeline integrity. In the project reported in this paper, samples that had been machined from a large-diameter welded gas transmission pipe were subjected to slow strain rate testing (SSRT) at different strain rates in a soil solution and in NS4 solution, both purged with 5% CO2/balance N2 gas mixture. There were many more quasi-cleavage areas on the fracture surfaces of the weld HAZ specimens than on the fracture surfaces of the base metal. The increased SCC susceptibility of the weld HAZ samples compared to the base steel was attributed to the coarse-grained, non-uniform microstructure of the HAZ samples as well as the higher residual stress. SCC propensity increased with decreasing loading rate and with more negative potentials. SCC initiation was associated with pitting corrosion.

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: 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
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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