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Record W2899711637 · doi:10.1115/ipc2018-78392

Differences in Near-Neutral pH Crack Growth Behavior Between Oil Pipelines and Gas Pipelines and Corresponding Crack Growth Mitigation Strategies

2018· article· en· W2899711637 on OpenAlexafffund
Zhezhu Xu, Andrea Daniel, Karina Chevil, Erwin Gamboa, Weixing Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsTransCanada (Canada)University of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPipeline transportCorrosionMaterials scienceCrackingPetroleum engineeringStress corrosion crackingDissolutionFossil fuelRange (aeronautics)Composite materialEnvironmental scienceMetallurgyGeologyChemistryEnvironmental engineeringWaste managementEngineering

Abstract

fetched live from OpenAlex

Oil pipelines and gas pipelines operations result in very different pressure fluctuation schemes due to different compressive properties of liquids and gases. Liquid fluids such as oil are less compressible and pressure fluctuations during oil pipelines operations are more frequent and vary over a wide range of magnitudes and frequencies, compared with those during gas pipelines operations. Despite the differences in operating conditions indicated above, both oil pipelines and gas pipelines are susceptible to stress corrosion cracking and corrosion fatigue failures. This investigation was initiated to understand the different crack growth rate behavior of pipeline steels characteristic to the type of pressure fluctuation schemes in near-neutral pH environment, that is, oil pipelines vs. gas pipelines. It was suspected that the similar range of service life between oil pipeline steels and gas pipeline steels could be attributed to a higher rate of direct dissolution at the tip of a crack during gas pipeline operation because of much higher mean pressures, despite their lower crack growth caused by corrosion fatigue. In the case of near-neutral pH stress corrosion cracking, corrosion makes minor contribution to crack growth but produces diffusible hydrogen that interacts with cyclic loading to make cracks grow. This study was performed using specimens with surface cracks, which simulated the following two environmental conditions: 1) fully exposed to the environment, 2) shielded from the environment, exposed to hydrogen only. In Case 1), the specimen surface, on which the surface cracks were made, was fully exposed to a near-neutral pH solution, allowing the occurrence of corrosion at the crack tip. In Case 2), a narrow strip of a coating was applied to prevent the cracks from direct contact with the corrosive solution; however, the cracks were affected by diffusible hydrogen which had been generated as a by-product of corrosion on the adjacent steel surface free of coatings. These specimens were mechanically loaded under different pressure schemes typical of both oil and gas pipeline operations. It has been found that crack growth caused by direct dissolution of crack tip materials is insignificant, regardless of pipeline operating conditions. A much higher crack growth rate, attributed to hydrogen embrittlement, was found under gas transmission conditions, while a higher corrosion fatigue crack growth was found under oil transmission conditions. Based on these findings, strategies on crack growth mitigation, characteristic to each type of pipeline operation are also proposed.

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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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