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Bounding Surface Constitutive Model for Cemented Sand under Monotonic Loading

2015· article· en· W1898705296 on OpenAlexafffund
Mojtaba Rahimi, Dave Chan, Alireza Nouri

Bibliographic record

VenueInternational Journal of Geomechanics · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Alberta
FundersNational Research Council CanadaNational Science Council
KeywordsYield surfaceConstitutive equationGeotechnical engineeringMonotonic functionVoid ratioMaterials scienceStress pathPlasticityUltimate tensile strengthVoid (composites)Cohesion (chemistry)StiffnessElastic modulusPore water pressureStructural engineeringMechanicsFinite element methodComposite materialGeologyMathematicsEngineeringMathematical analysis

Abstract

fetched live from OpenAlex

This paper presents a critical state constitutive model for cemented sand. The model uses a single capped yield surface as a function of the void ratio, confining pressure, preconsolidation pressure, and stress ratio at the peak of the undrained effective stress path. To model the cemented materials, the formulation of the yield function, elastic moduli, plastic modulus, flow rule, and other components of the model have been modified. Having incorporated the tensile strength and cohesion, the radial-mapping formulation of the bounding surface plasticity is incorporated in the model. The modified model has been calibrated and verified based on experimental results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.266
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations61
Published2015
Admission routes2
Has abstractyes

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