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Record W2005056225 · doi:10.1680/geot.12.p.010

Numerical modelling of a field desiccation test

2013· article· en· W2005056225 on OpenAlexaboutno aff
Aruna L. Amarasiri, Jayantha Kodikara

Bibliographic record

VenueGéotechnique · 2013
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsDesiccationNumerical modelsField (mathematics)Geotechnical engineeringComputer simulationLaboratory testFinite element methodEngineeringStructural engineeringGeologyEcologyMathematicsBiochemical engineeringSimulationBiology

Abstract

fetched live from OpenAlex

The numerical modelling of a field desiccation experiment carried out in Saint Alban, Canada is attempted. The progression of cracks during the course of desiccation and most material properties relevant to the modelling have been reported in detail in the published literature. The numerical model is based on the cohesive crack approach using a distinct-element program. The model seeks to replicate the crack pattern obtained in a linear section of the experiment. The development of the primary crack network is modelled successfully. The methodology shown in the paper can be used for numerical modelling of field desiccation.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.192
Teacher spread0.173 · 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

Citations24
Published2013
Admission routes1
Has abstractyes

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