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Record W2083881562 · doi:10.1002/2014jb011064

Influence of microscale heterogeneity and microstructure on the tensile behavior of crystalline rocks

2014· article· en· W2083881562 on OpenAlexaff
O. K. Mahabadi, B. S. A. Tatone, Giovanni Grasselli

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2014
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGeomechanica (Canada)University of Toronto
Fundersnot available
KeywordsMicroscale chemistryMaterials scienceUltimate tensile strengthBrittlenessMicrostructureFracture (geology)Composite materialStress (linguistics)Computer simulationPhase (matter)MechanicsMathematics

Abstract

fetched live from OpenAlex

Abstract This study investigates the influence of microscale heterogeneity and microcracks on the failure behavior and mechanical response of a crystalline rock. The thin section analysis for obtaining the microcrack density is presented. Using micro X‐ray computed tomography (μCT) scanning of failed laboratory specimens, the influence of heterogeneity and, in particular, biotite grains on the brittle fracture of the specimens is discussed and various failure patterns are characterized. Three groups of numerical simulations are presented, which demonstrate the role of microcracks and the influence of μCT‐based and stochastically generated phase distributions. The mechanical response, stress distribution, and fracturing process obtained by the numerical simulations are also discussed. The simulation results illustrate that heterogeneity and microcracks should be considered to accurately predict the tensile strength and failure behavior of the sample.

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)0.001
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
Metaresearch0.0000.001
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)0.0010.000

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 head0.021
GPT teacher head0.296
Teacher spread0.275 · 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

Citations175
Published2014
Admission routes1
Has abstractyes

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