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Record W4366963996 · doi:10.1051/e3sconf/202338212001

3-Dimensional Numerical Evaluation of Geosynthetic Encased Stone Columns in Unsaturated Soils

2023· article· en· W4366963996 on OpenAlexaff
Mohammed Shakeel Abid, G. Venkata Ramana, Sai K. Vanapalli, Kasinathan Muthukkumaran

Bibliographic record

VenueE3S Web of Conferences · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGeotechnical engineeringSuctionSoil waterStiffnessBoundary (topology)GeologyMaterials scienceSoil scienceEngineeringMathematicsComposite materialMechanical engineering

Abstract

fetched live from OpenAlex

Geosynthetic encased stone columns are often designed using the conventional framework of saturated soils ignoring the influence of in-situ unsaturated soil conditions. This article evaluates the performance of stone columns with and without geosynthetic encasement extending the mechanics ofunsaturated soils. The focus of numerical simulations was directed towards understanding the influence of matric suction on the confining support offered by the surrounding soil to stone columns with and without geosynthetic encasement. Investigations were extended considering the stiffness and the length of the geosynthetic encasement. The numerical studies suggest the load-carrying capacity of stone columnincreased with an increase in the matric suction in the boundary effect and the primary transition zone. However, the contribution of matric suction towards load-carrying capacity starts reducing from the secondary transition zone. The information on boundary effect and transition zones can be derived fromthe soil-water characteristic curve, which is a relationship between the water content and soil suction. In addition, the effect of stiffness and length of encasing material in unsaturated soils was found to be in contrast with saturated soils. The results of the study are promising towards developing procedures thatcan be used in the rational design of stone columns in unsaturated soils.

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)0.001
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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.257
Teacher spread0.230 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

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