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Record W2123029684 · doi:10.1139/t07-112

A new modelling approach for unsaturated soils using independent stress variables

2008· article· en· W2123029684 on OpenAlexaffvenue
Daichao Sheng, D. G. Fredlund, Antonio Gens

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsSoil waterGeotechnical engineeringSlurrySuctionHardening (computing)WettingShrinkageCritical state soil mechanicsGeologyConstitutive equationEnvironmental scienceSoil scienceMaterials scienceEngineeringEnvironmental engineeringComposite materialFinite element methodStructural engineering

Abstract

fetched live from OpenAlex

Although a number of constitutive models for unsaturated soils exist in the literature, some fundamental questions have not been fully answered. There are questions related to (i) the change of the yield stress with soil suction, (ii) modelling slurry soils, and (iii) the smooth transition between saturated and unsaturated soil states. This paper addresses these questions by proposing an alternative modelling approach. The paper first presents a volumetric model for unsaturated soils. This volumetric model is then used to derive the yield surface in the suction – mean stress space. Hysteresis associated with soil-water characteristic curves is then formulated in the same framework of elastoplasticity. It is shown that volume collapse during wetting and plastic shrinkage during initial drying are both direct results of a suction-dependent hardening law. The proposed model seems to be more flexible in modelling different types of unsaturated soils than most models in the literature. The model can be applied to soils that are dried or loaded from initially slurry conditions, for soils that have low to high air-entry values, and for compacted soils as well.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.032
GPT teacher head0.210
Teacher spread0.178 · 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

Citations346
Published2008
Admission routes2
Has abstractyes

Explore more

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