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A comparison of hydrogen permeation and the resulting corrosion enhancement of X65 and X80 pipeline steels

2014· article· en· W2025830172 on OpenAlexaff
Xingyu Peng, Y. Frank Cheng

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2014
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceCorrosionHydrogenMetallurgyHydrogen embrittlementElectrochemistryPermeationNuclear chemistryChemistryPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

In this work, corrosion and electrochemical hydrogen permeation behaviour of two grades of pipeline steel, X65 and X80 steels, were investigated by hydrogen-charging, electrochemical impedance spectroscopy measurements and metallographic observation. It was found that the corrosion and hydrogen permeation behaviour of steels is affected by their metallurgical features. Upon hydrogen-charging, both high grade of X80 pipeline steel and low grade of X65 steel show enhanced corrosion activity. The electrochemical hydrogen permeation current measurements and calculations show that the X80 steel contains a higher density of hydrogen traps than X65 steel, which may potentially result in the increased susceptibility of X80 steel to hydrogen-induced cracking (HIC).Dans ce travail, la corrosion électrochimique de l’hydrogène et un comportement de perméation de deux qualités d’acier de pipeline, X65 et X80 aciers, ont été étudiés par l'hydrogène charge, électrochimiquemesures de spectroscopie d’impédance et l’observation métallographique. On a constaté que lela corrosion et de l’hydrogène comportement de perméation des aciers est affectée par leurs caractéristiques métallurgiques.Sur hydrogène charge, à la fois de haute qualité en acier de pipeline X80 et X65 de bas grade de spectacle en acierune activité améliorée à la corrosion. L'hydrogène perméation électrochimique des mesures de courantet les calculs montrent que l’acier X80 contient une plus grande densité de pièges à hydrogène de X65acier, ce qui peut potentiellement entraîner l’augmentation de la sensibilité de l’acier X80 pour induite par l’hydrogène; Fissuration (HIC).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.095
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.017
GPT teacher head0.276
Teacher spread0.259 · 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.

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

Citations12
Published2014
Admission routes1
Has abstractyes

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