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Record W2117137107 · doi:10.1002/nag.555

Analysis of liquefaction susceptibility of nearly saturated sands

2006· article· en· W2117137107 on OpenAlexafffund
Ahmad Jafari‐Mehrabadi, Majid Abedinzadegan Abdi, Radu Popescu

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2006
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaPrinceton University
KeywordsConstitutive equationLiquefactionSaturation (graph theory)Geotechnical engineeringCompressibilitySoil waterSoil liquefactionPlasticityFinite element methodGeologyDissolutionMechanicsEngineeringMathematicsThermodynamicsPhysicsSoil scienceStructural engineering

Abstract

fetched live from OpenAlex

Abstract A new constitutive formulation for simulating the behaviour of nearly saturated sands under seismic loads is presented. The formulation is based on combining the Henry's law for dissolution of gas in water, the ideal or perfect gas law and the law of conservation of mass. The effects of transient air dissolution in water on the compressibility of partially saturated soils are also taken into account. The model was calibrated based on numerical simulations of isotropically consolidated cyclic triaxial tests conducted on partially saturated samples of Toyoura sand. A multi‐yield plasticity soil constitutive model implemented in the finite element code DYNAFLOW was used for these numerical simulations. It is shown that the formulation proposed here is able to reasonably predict the soil cyclic undrained behaviour at various degrees of saturation (95% and higher). Copyright © 2006 John Wiley & Sons, Ltd.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.335
Teacher spread0.319 · 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
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

Citations7
Published2006
Admission routes2
Has abstractyes

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