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Record W3096851309 · doi:10.1080/02670836.2020.1839205

Visualisation of diffusion sites and measurement of hydrogen traps in hot-rolled pipes

2020· article· en· W3096851309 on OpenAlex
Alen Thomas, Jerzy A. Szpunar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials Science and Technology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceDiffusionHydrogenPermeationMicrostructureDiffusion layerDiffusion processPermeability (electromagnetism)Layer (electronics)MetallurgyComposite materialThermodynamicsChemistry

Abstract

fetched live from OpenAlex

Inclusions are very often founded in the centre of thickness in hot-rolled pipeline steel. In this research, the role of these inclusions on hydrogen diffusion, accumulation and distribution in pipeline steel is studied using the electrochemical permeation and visualisation experiments. While the permeation experiment estimates the parameters of the diffusion process, the visualisation experiment reveals the diffusion pathway in the steel microstructure. Results from the permeation test allowed to show that the steel samples selected from the segregation zone at the mid-layer of thickness have higher permeability and effective diffusion coefficient than samples from the top-layer. Also, the hydrogen visualisation results permit to reveal an increased discharge of hydrogen around inclusions as represented by a pattern of superimposed white particles. Moreover, the calculated diffusion parameters also allowed us to establish that the density of hydrogen traps in mid-layer was lower than top-layer of the steel.

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.

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 score0.005
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.264
Teacher spread0.234 · 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