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Record W4386523241 · doi:10.56952/arma-2023-0955

The Use of Digital Image Correlation (DIC) to Investigate the Effect of Layering and Bedding Plane Orientations on Young's Modulus and Poisson's Ratio Measurements of Buckinghorse Shale Samples

2023· article· en· W4386523241 on OpenAlexaff
Bezawit F. Haile, Earl Magsipoc, Giovanni Grasselli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDigital image correlationExtensometerLayeringBedGeologyModulusPoisson's ratioAnisotropyBeddingDisplacement (psychology)Materials scienceLateral strainYoung's modulusDeformation (meteorology)MineralogyGeotechnical engineeringPoisson distributionComposite materialOpticsMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Anisotropy due to heterogeneities in rocks, such as shale, affects the mechanical properties of the rock depending on their orientation and arrangement. For instance, layering and pre-existing cracks can create potential weak planes. Hence, a measurement technique that can capture spatially detailed deformation, such as digital image correlation (DIC), is important for the investigation of the effect of rock heterogeneities. This technique enables a larger field of view than conventional strain gauges measurements. In this study, the effect of bedding planes on the macroscopic failure patterns of shale samples from the Buckinghorse Formation was investigated using unconfined compressive strength (UCS) tests. The DIC analysis showed areas of displacement discontinuity and localized strain caused by bedding plane orientation, and that layering has a significant effect on the Young's modulus computation based on the location of sampling and the length of measurement. With load perpendicular to the bedding, the Young's modulus showed significant variance even when measuring across large portions of the sample. As the virtual extensometer length increased, localized effects were smoothed, and the values approached the strain and Young's moduli from the LVDT instrumentation. While the variance of the calculated Poisson's ratio measured along different loading orientations appeared consistent, the stress-strain plots using horizontal virtual extensometers (lateral strain) presented more details on lateral differences with respect to location. Hence, it was shown that local variability in stiffness could potentially affect the mechanical characterization of rocks with strong heterogeneities. DIC analysis, which captures this variability, should be used to complement conventional laboratory instrumentation. INTRODUCTION Rocks have various heterogeneities that may affect their mechanical properties. Shale exhibits a transverse isotropic elastic response due to layering from sedimentation. The Buckinghorse shale formation, which is a dark gray shale formation found as part of the Lower Cretaceous shales in northeastern British Columbia (BC) (Chalmers and Bustin, 2008) was selected to be used in this study.

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)0.001
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 score0.349
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.100
GPT teacher head0.293
Teacher spread0.193 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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