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Record W2581281702 · doi:10.1063/1.4974149

Rotary shear experiments under X-ray micro-computed tomography

2017· article· en· W2581281702 on OpenAlexafffund
Qi Zhao, Nicola Tisato, Giovanni Grasselli

Bibliographic record

VenueReview of Scientific Instruments · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCarbon Management CanadaUniversity of TorontoCanada Foundation for Innovation
KeywordsShearing (physics)Materials scienceTomographyShear (geology)Deformation (meteorology)Computed tomographySample (material)X-rayComposite materialMechanicsOpticsPhysics

Abstract

fetched live from OpenAlex

A rotary shear apparatus (ERDμ-T) was designed, assembled, and calibrated to study frictional behavior. We paired the apparatus with X-ray micro-computed tomography (μCT) to inspect in situ and in operando deformation of the tested specimen. This technology allows us to observe how two rough surfaces interact and deform without perturbing the experimental conditions (e.g., pressure, temperature, and sample position). We performed an experiment employing an aluminum alloy sample to demonstrate the capability of the apparatus. The sample was sheared at incremental steps, and during shearing, normal force, sample shortening, torque, and shearing velocity were measured. The measurements were associated to the μCT imagery, giving a comprehensive understanding of the deformation processes of the samples. The present contribution demonstrates that the ERDμ-T allows (1) linking the variation of physical parameters to the evolution of internal structures of the sample and (2) shedding light on fracturing and frictional sliding processes in solid materials.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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 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

Citations13
Published2017
Admission routes2
Has abstractyes

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