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Record W4395666133 · doi:10.3390/ma17092026

Effect of Fusion Boundary Microstructure on Flow-Accelerated Corrosion Cracking

2024· article· en· W4395666133 on OpenAlexafffund
Yajing Wang, Zhe Lyu, Zhisheng Wu, Leijun Li

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Alberta
FundersMitacs
KeywordsMicrostructureMaterials scienceCrackingFusionCorrosionMetallurgyComposite material

Abstract

fetched live from OpenAlex

Flow-accelerated corrosion (FAC) preferentially attacks the downstream heat-affected zone of the root-pass weld in steam pipe systems. A detailed characterization identifies the fusion boundary as the initiation location for the attack. Alloying elements are found depleted along the weld fusion boundary, and multiple welding thermal cycles and repetitive austenite-to-ferrite phase transformations result in an increased proportion of grains with Goss {110}<001> texture along the fusion boundary. The synergistic effects of chemical segregation and the Schmid factor may contribute to the preferential initiation of FAC cracks along the root weld fusion boundary, making it the weakest link for FAC attack in steam pipe girth welds.

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 head0.010
GPT teacher head0.265
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".

Quick stats

Citations3
Published2024
Admission routes2
Has abstractyes

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