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Record W2944922339 · doi:10.24423/aom.3084

State-dependent fractional plasticity model for the true triaxial behaviour of granular soil

2018· article· en· W2944922339 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

VenueOpen MIND · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsPlasticityStress spaceGranular materialFractional calculusTriaxial shear testMathematicsGeotechnical engineeringStress (linguistics)Flow (mathematics)Soil waterMechanicsMaterials scienceMathematical analysisGeometryPhysicsGeologyConstitutive equationThermodynamicsFinite element methodComposite materialShear (geology)Soil science

Abstract

fetched live from OpenAlex

The fractional plasticity was proposed to model the stress-strain behaviour of granular soils, but only within the scope of classical triaxial loading condition. In this study an attempt is made to develop a 3D fractional plasticity model for granular soils subjected to true triaxial loads by using characteristic stress, where all the fractional-order and integer-order derivatives can be easily obtained. Without using a plastic potential, the non-associated plastic flow rule is achieved by performing fractional derivatives of the yielding function in the characteristic stress space. The obtained plastic flow direction is found to be influenced by the fractional order, characteristic stress parameter and intermediate stress ratio. To further validate the proposed model, a series of true triaxial test results of different granular soils are simulated, from which good agreement between the model predictions and the corresponding test results is found.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score0.328

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 head0.032
GPT teacher head0.265
Teacher spread0.233 · 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