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Experimental study of microstructural pathways for hydrogen-induced damage in X80 line pipe steel weld

2025· article· en· W4415342997 on OpenAlexaff
Nemat Amirjani, Ehsan Entezari, Jerzy A. Szpunar, A.G. Odeshi, Amrita Bag, Muhammad Rashid

Bibliographic record

VenueEngineering Failure Analysis · 2025
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of ReginaUniversity of Saskatchewan
Fundersnot available
KeywordsCharpy impact testAcicular ferriteCementiteFerrite (magnet)MartensiteHydrogen embrittlementHydrogenWelding

Abstract

fetched live from OpenAlex

• Hydrogen damage in X80 pipe weld via electrochemical and low-temperature Charpy impact tests were studied. • ALF and AF interface, and TM and BF were more susceptible to hydrogen-induced damage. • Non-uniform kernel average misorientation increased susceptibility to hydrogen-induced damage. • Al 2 O 3 and MnS inclusions with (Nb, Ti) (C, N) precipitates were observed in crack pathway. • Steels with lower low-temperature toughness were more susceptible to hydrogen-induced degradation. Microstructural features responsible for hydrogen-induced damage in X80 linepipe weld were systemically investigated through quantitative microstructural analysis, electrochemical hydrogen charging, hydrogen microprint and permeation techniques, and corrosion testing. Additionally, Charpy V-notch impact tests were conducted over a temperature range from 0 °C to −65 °C. The results showed that the fusion zone and fusion line, especially in the weld middle were the most susceptible to hydrogen-induced cracking, blistering, and micro pitting. These damages primarily occured at allotriomorphic ferrite and acicular ferrite interfaces in the fusion zone, and tempered martensite and bainitic ferrite in the fusion line, where increased hydrogen accumulation was observed. Significant differences in kernel average misorientation (KAM) between allotriomorphic ferrite and acicular ferrite, along with elevated KAM value in bainitic ferrite and tempered martensite, contributed to enhanced hydrogen trapping density in the weld metal. The morphology of cementite was also detrimental, as shown by tempered martensite with spheroidal cementite trapping comparatively less hydrogen than bainitic ferrite containing lamellar cementite. Non-metallic inclusions (Al 2 O 3 , MnS) and (Nb, Ti) (C, N) carbides were also present along the crack path. Compared to the base metal, the weld metal, i.e. fusion zone and fusion line, exhibited higher density of hydrogen-trapping sites (3.44 × 10 +21 vs. 1.50 × 10 +21 cm −3 ) and greater hydrogen solubility (2.22 × 10 −4 vs. 1.18 × 10 −4 mol. cm −3 ), along with accelerated corrosion rate (0.8 vs. 0.09 mm/year). Additionally, the weld metal showed poorer low-temperature toughness in the non-hydrogen-charged condition. This reduced toughness was associated with a higher susceptibility to hydrogen-related degradation, highlighting the influence of microstructure on weld performance under hydrogen exposure.

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 score0.005

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)0.0020.000

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 head0.270
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 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".

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Citations1
Published2025
Admission routes1
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