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Record W2299107892 · doi:10.1680/ijpmg.2002.020102

Characterization of failure in sand under triaxial compression using an industrial X-ray CT scanner

2002· article· en· W2299107892 on OpenAlexaff
Jun Otani, Toshifumi Mukunoki, Yuzo Obara

Bibliographic record

VenueInternational Journal of Physical Modelling in Geotechnics · 2002
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsQueen's University
Fundersnot available
KeywordsScannerTriaxial shear testCompression (physics)Geotechnical engineeringNondestructive testingComputed tomographyCharacterization (materials science)TomographyX-rayMaterials scienceEngineeringStructural engineeringComputer scienceComposite materialPhysicsArtificial intelligenceOpticsRadiology

Abstract

fetched live from OpenAlex

A new triaxial compression test apparatus was developed for use with an industrial X-ray computed tomography (X-ray CT) scanner and used to characterize progressive failure with strain localization in sand. Performance of the new triaxial compression apparatus was verified separately prior to use within an X-ray CT scanner system. High quality visualizations obtained from a series of nondestructive tests conducted under triaxial compression with the new test apparatus made it possible to visually characterize progressive failure with propagating strain localization in a soil specimen using three-dimensional CT images. Specifications for the new apparatus and procedures for its use were established and potential applications and avenues of further research were discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.499

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 studies0.0000.000
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 head0.056
GPT teacher head0.260
Teacher spread0.204 · 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 designSimulation or modeling
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

Citations55
Published2002
Admission routes1
Has abstractyes

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