MétaCan
Menu
Back to cohort
Record W1970006986 · doi:10.2320/jinstmet.71.181

Measurement of 3-D Strain Distribution by means of High-Resolution X-ray CT Image and Tracking of Microstructural Features

2007· article· en· W1970006986 on OpenAlexaff
Masakazu Kobayashi, Hiroyuki Toda, Yuji Kawai, Toshirō Kobayashi, Kentaro Uesugi, David S. Wilkinson, Éric Maire, Yoshimitsu Aoki

Bibliographic record

VenueJournal of the Japan Institute of Metals and Materials · 2007
Typearticle
Languageen
FieldComputer Science
TopicComputational Geometry and Mesh Generation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTracking (education)Materials scienceSynchrotron radiationDeformation (meteorology)TomographyUltimate tensile strengthResolution (logic)SynchrotronOpticsComposite materialMineralogyPhysicsGeologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Measurement of interior strain distribution has been developed based on the synchrotron radiation computed tomography (SR-CT). In metal deformation, local strain distribution differs from macroscopic strain due to microstructural factors such as grains, grain boundaries, particles, pores, voids, and cracks. A model sample, which was made from a copper alloy strengthened with alumina, was prepared containing artificial pores. Tensile loading was applied to the sample step by step. High-resolution tomographic experiment was performed at the third-generation synchrotron radiation facility (SPring-8) in Japan. Gravity center position, volume and surface area in the pores, which were regarded as markers in a tracking procedure, were measured by 3-D digital image analysis in the SR-CT images. The markers before and after the deformation were provided for registration and macroscopic strain correction before the tracking procedure. The marker tracking was carried out by means of matching parameter that was described as functions of distance, volume and surface at markers. The ratio of success tracking was evaluated in order to clarify whether the tracking method developed in this study was reliable. The 3-D strain distribution was represented successfully by the tracking results. A combination of high-resolution SR-CT and tracking of microstructural features is effective to visualize interior strain distribution in materials in 3-D.

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)0.002
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 score0.087
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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.

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

Citations7
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Japan Institute of Metals and MaterialsSame topicComputational Geometry and Mesh GenerationFrench-language works237,207