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Texture heterogeneities in α<sub>p</sub>/α<sub>s</sub> titanium forging analysed by EBSD‐Relation to fatigue crack propagation

2009· article· en· W2061449040 on OpenAlexaff
Elena Uta, Nathalie Gey, Philippe Bocher, Michel Humbert, J. Gilgert

Bibliographic record

VenueJournal of Microscopy · 2009
Typearticle
Languageen
FieldMaterials Science
TopicTitanium Alloys Microstructure and Properties
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsElectron backscatter diffractionMaterials scienceForgingNucleationMicrostructureTexture (cosmology)DiffractionPole figureCrystallographyCleavage (geology)Composite materialMetallurgyOpticsFracture (geology)PhysicsChemistryImage (mathematics)

Abstract

fetched live from OpenAlex

The microstructure and the local texture of a large IMI 834 forging were characterized using the Electron Back Scattered Diffraction (EBSD) technique. Crystallographic domains called macrozones and formed by a majority of primary alpha(p) grains with their axes in nearly the same direction were found. They had a band-like structure, parallel to the axial direction of the forging. The influence of these macrozones on the cold dwell-fatigue properties was studied. Several samples were tested under cold dwell-fatigue conditions. The crack initiation and the short-distance propagation region optically matched a bright region that contained numerous quasi-cleavage facets. The analysis of the EBSD measurements showed that this bright region was enclosed within a sharp textured region with axes at less than 30 degrees from the loading axis. The crystallographic features of the crack nucleation site and the crack propagation path were also analysed.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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)0.0010.000

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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 designObservational
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

Citations102
Published2009
Admission routes1
Has abstractyes

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