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Localization of Deformation in Anisotropic Granular Materials Utilizing the Microstructure Tensor

2021· article· en· W3158206837 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Geomechanics · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAnisotropyMicrostructureShear bandSimple shearShear (geology)Tensor (intrinsic definition)Materials sciencePrincipal axis theoremPlasticityStrain rate tensorEigenvalues and eigenvectorsDeformation (meteorology)Classical mechanicsGeometryMechanicsCauchy stress tensorPhysicsComposite materialMathematicsOptics

Abstract

fetched live from OpenAlex

The shear band formation and orientation in anisotropic granular materials have been studied. The anisotropy is described by making use of the microstructure tensor that complies with principles of continuum mechanics and expresses the anisotropy in a coordinate-invariance form. Further studies are conducted, based on bifurcation analysis, to investigate the conditions for the initiation and orientation of the shear band in anisotropic granular materials. The role of parameters describing the material anisotropy in shear band formation is examined. The main focus of this study is to relate principal values and directions of the microstructure tensor with the condition of localization of the deformation into a shear band. In particular, the influence of eigenvalues and eigenvectors of the microstructure tensor have been studied based on the classical theory of plasticity.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score0.295

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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