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Numerical Modeling on the Stress-Strain Behavior of Sand via Disturbed State Concept Model

2017· article· en· W2743484024 on OpenAlex

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKey engineering materials · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringMaterials scienceHardening (computing)SofteningConstitutive equationStress (linguistics)Triaxial shear testStress–strain curveStrain hardening exponentDisturbance (geology)Deformation (meteorology)Composite materialStructural engineeringFinite element methodGeologyEngineering

Abstract

fetched live from OpenAlex

The disturbed state concept (DSC), proposed by Desai, is a powerful constitutive modeling for the simulation of the material behaviors of strain hardening or softening of soil. These material parameters can be decided by the results of the triaxial compression test of soil. Some triaxial drained test were performed to obtain the deviator stress vs. axial strain behaviors of Ottawa sand with relative densities D r =20% and 90% under three different confining pressures. The result shows that the experimental data and the results of the DSC model showed good correspondence. In study for disturbance parameters to effect on the curve of axial strain vs. deviator stress, it can be found that the deviator stress after peak markedly decreases when the values of disturbance parameters are reduced. The effect of disturbance parameter A on the trend for deviator stress decrease after peak is higher than that of parameter B.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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