MétaCan
Menu
Back to cohort
Record W2123910606 · doi:10.1139/t08-057

An improved elastic–viscoplastic soil model

2008· article· en· W2123910606 on OpenAlexaffvenue
Curtis Kelln, Jitendra Sharma, David Hughes, J. Graham

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
Fundersnot available
KeywordsViscoplasticityCreepGeotechnical engineeringPlasticityStress relaxationViscoelasticityMaterials scienceMechanicsElasticity (physics)Pore water pressureGeologyConstitutive equationStructural engineeringPhysicsEngineeringFinite element methodComposite material

Abstract

fetched live from OpenAlex

This paper develops an improved and accessible framework for modelling time-dependent behaviour of soils using the concepts of elasticity and viscoplasticity. The mathematical description of viscoplastic straining is formulated based on a purely viscoplastic and measurable phenomenon, namely creep. The resulting expression for the viscoplastic strain rates includes a measure of both effective stress and the corresponding volumetric packing of the soil particles. In this way, the model differs from some earlier viscoplastic models and arguably provides a better conceptual description of time-dependent behaviour. Analytical solutions are developed for the simulation of drained and undrained strain-controlled triaxial compression tests. The model is then used to back-analyze the measured response of normally consolidated to moderately overconsolidated specimens of a soft estuarine soil in undrained triaxial compression. The model captures aspects of soil behaviour that cannot be simulated using time-independent elastic–plastic models. Specifically, it can capture the dependence of stress–strain relationships and undrained shear strength on strain rate, the development of irrecoverable plastic strains at constant stress (creep), and the relaxation of stresses at constant strain.

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)0.000
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: none
Teacher disagreement score0.840
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 integrity0.0000.001
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 head0.009
GPT teacher head0.183
Teacher spread0.173 · 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.

Study designSimulation or modeling
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

Citations65
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207