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Record W2462831186 · doi:10.1139/cgj-2015-0049

Unifying framework for modeling swelling soil behaviour

2016· article· en· W2462831186 on OpenAlexaffvenue
Bee Fong Lim, Greg Siemens

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsExpansive claySwellingGeotechnical engineeringSoil waterAtterberg limitsSwellExpansiveWettingPlasticityClay soilSoil scienceMaterials scienceGeologyThermodynamicsComposite materialPhysics

Abstract

fetched live from OpenAlex

The destructive effect of expansive soils on infrastructure is one of the classical issues associated with unsaturated soils. Given the continuing challenges associated with swelling soils there is still a need for a practical analysis method. The swelling equilibrium limit (SEL) provides a concept for modeling expansive soil behaviour. The SEL is an upper bound swelling limit, which depends on the soil’s initial state and the boundary conditions upon wetting. The SEL is obtained experimentally from swelling tests performed by applying a range of swelling scenarios from rigid boundary condition to free swelling without confinement. In this paper, improvements to the triaxial swelling apparatus are reported, SELs for two new swelling soils are characterized, and a framework for SEL prediction is developed. The SEL framework is developed to relate SEL parameters to index properties as well as the soil’s initial volume. SEL parameters are correlated to liquid limit, plasticity index, free swell potential, and specific volume. The relationships are used to estimate the SEL for Regina clay, which is shown to agree with experimental data.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.021
GPT teacher head0.228
Teacher spread0.206 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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