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Record W2005385897 · doi:10.1139/t08-048

Hydrostatic compression model for sandy soils

2008· article· en· W2005385897 on OpenAlexvenueno aff
Javier Vallejos

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsHydrostatic equilibriumVoid ratioBreakageGeotechnical engineeringCompressibilitySoil waterStiffnessCompression (physics)Void (composites)MechanicsHydrostatic stressMaterials scienceEffective stressGeologyStructural engineeringSoil scienceFinite element methodComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Based on elastic considerations, a new four parameter model of the hydrostatic compression curves of sandy soils is presented. Using a unique set of parameters, this model is capable of accurately representing the infinite family of compression curves that result when soil is subjected to stresses below particle breakage. The parameters are readily estimated from two hydrostatic tests conducted at different initial densities during loading and unloading stages. The resulting equations are able to predict the effect of progressive stiffness increase and compressibility reduction that occur as void ratio decreases during both loading and unloading conditions. The same normalized stress scale employed for the hydrostatic compression curves can also be used to describe the steady state line, which leads to a unique framework for representing the stress–void ratio curves of sandy soils. A comprehensive series of simulations on 13 different types of sandy soils in both loose and dense states was performed under a wide range of mean stresses during loading and unloading conditions. The simulations gave very satisfactory agreement with published 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 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 score0.942
Threshold uncertainty score0.806

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 integrity0.0000.001
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 head0.020
GPT teacher head0.205
Teacher spread0.185 · 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
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

Citations21
Published2008
Admission routes1
Has abstractyes

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