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Record W4409500483 · doi:10.5006/c2024-20914

Insulation Driven Intergranular Stress Corrosion Cracking of Carbon Steel

2024· article· en· W4409500483 on OpenAlexaboutno aff
Matt Krantz, Yuan Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsnot available
Fundersnot available
KeywordsIntergranular corrosionStress corrosion crackingMaterials scienceCrackingMetallurgyStress (linguistics)Carbon fibersCorrosionComposite material

Abstract

fetched live from OpenAlex

Abstract Over the past decade, an increasing number of intergranular stress corrosion cracking (IGSCC) incidents have been observed on carbon steel assets operating in Alberta, Canada. At the time of publication, over 128 distinct cracks have been identified on 26 assets spanning at least 5 operators. All incidents have occurred on uncoated carbon steel operating between 70 °C and 190 °C and exposed to wet mineral wool insulation. Both piping and pressure vessels have been affected. Cracking has been isolated to assets with mineral wool insulation produced after 2003; however, a specific change to mineral wool composition in this timeframe has not been identified. The purpose of this paper is to provide a summary of incidents and investigations that have been reported to date and to update the environmental conditions (window of susceptibility) where insulation driven intergranular stress corrosion cracking has been observed. By drawing attention to this issue, it is the authors' objective to increase awareness and determine if similar cracking incidents are occurring in other geographical regions.

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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.275
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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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