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Record W4243823014 · doi:10.2495/978-1-78466-249-3/002

Studies of microscopic strains on Alloy 600 surfaces arising from stress-corrosion cracking

2017· book-chapter· en· W4243823014 on OpenAlexafffund
N. S. McIntyre, Todd W. Simpson, Jun Qin, Nathaniel Sherry, M. Bauer, Jaganathan Ulaganathan, Anatolie G. Carcea, R. C. Newman, Martin Kunz, Nobumichi Tamura

Bibliographic record

VenueWIT transactions on state-of-the-art in science and engineering · 2017
Typebook-chapter
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of TorontoWestern University
FundersNatural Sciences and Engineering Research Council of CanadaBasic Energy SciencesUniversité de NeuchâtelCANDU Owners GroupU.S. Department of Energy
KeywordsStress corrosion crackingMaterials scienceAlloyMetallurgyCorrosionStress (linguistics)CrackingComposite materialPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Microscopic distributions of elastic and plastic strains have been studied in Alloy 600 during accelerated corrosion. Laue diffraction is employed with a sub-micron beam of highly coherent polychromatic (white) radiation. The diffraction patterns are analysed to detect elastic and plastic deformations associated with the crack initiation and propagation processes. Stressed C-ring and unstressed mill annealed samples of Alloy 600 were corroded under hydrothermal, controlled electrochemical conditions. In the C-ring, the filamentous surface cracks produced had compressive strain fields along each crack. In the mill annealed sample, changes in strain fields in the same area were measured as oxidation progressed. Cracking at the metal grain boundaries appeared to be induced by expansive growth of surface oxides. For the mill annealed sample, accumulation of elastic strains in the grain boundaries appeared in advance of crack propagation.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.238
Teacher spread0.216 · 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 teacher head, not a consensus.

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
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueWIT transactions on state-of-the-art in science and engineeringSame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207