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Record W2118093538 · doi:10.1002/nag.881

Constitutive approach for rate‐sensitive anisotropic structured clays

2010· article· en· W2118093538 on OpenAlexafffundabout
Sean D. Hinchberger, Guangfeng Qu, K. Y. Lo

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConstitutive equationAnisotropyViscoplasticityViscosityIsotropyMaterials scienceStrain rateCompression (physics)Geotechnical engineeringTensor (intrinsic definition)MechanicsComposite materialThermodynamicsGeologyMathematicsPhysicsGeometryFinite element methodOptics

Abstract

fetched live from OpenAlex

Abstract This paper describes a constitutive approach to model the behavior of rate‐dependent anisotropic structured clay. Rate‐sensitivity is modeled using overstress viscoplasticity. Clay structure is treated as a viscous phenomenon whereby the viscosity of the undisturbed structured clay is initially very high and the viscosity degrades or decreases with plastic straining until the intrinsic or residual viscosity is reached. A microstructure tensor approach is used to make the structured viscosity anisotropic; whereas, the intrinsic viscosity is assumed to be isotropic. The behavior of the constitutive model is compared with the measured response of two clays (Gloucester and St. Vallier clay) from Eastern Canada during triaxial compression tests on specimens trimmed at different orientations to the vertical. The comparisons show that the constitutive framework is able to describe the anisotropic and rate‐sensitive response of both clays. The response of the model is also examined for the more general case of anisotropic consolidated triaxial compression and extension. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.777
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.019
GPT teacher head0.332
Teacher spread0.313 · 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
GenreMethods

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

Citations25
Published2010
Admission routes3
Has abstractyes

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