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Record W2767471562 · doi:10.1139/cgj-2017-0297

Wetting-induced collapse behavior of kaolinite: influence of fabric and inundation pressure

2017· article· en· W2767471562 on OpenAlexvenueno aff
Chinumani Choudhury, Tadikonda Venkata Bharat

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsKaoliniteOedometer testPore water pressureGeotechnical engineeringWettingSoil waterGeologyDewateringMaterials scienceMineralogyComposite materialSoil science

Abstract

fetched live from OpenAlex

Collapsible soils are known to withstand high normal stresses without undergoing a significant volume change in an air-dry state. The soil is, however, susceptible to a large volume change upon wetting. The volumetric collapse behavior of these soils is of great engineering interest to address the problem of ground subsidence. Kaolinite was found to be a collapsible soil similar to the loess soil. The collapse mechanism in kaolinite was due to changes in particle association (fabric) with the interaction with different pore fluids. Several physicochemical parameters strongly influenced the particle association by altering the charges on the particle surfaces and edges. The collapse nature of the kaolinite was investigated with great detail in this work. Wetting-induced collapse behavior of kaolinite was studied under the influence of pore-fluid chemistry using a multi-scale approach. The influence of pH, salt concentration, and dielectric pore-fluid environment on the clay behavior was analyzed using sedimentation and collapse tests. The collapse test results were well corroborated with the sedimentation test data, scanning electron microscopy images of lyophilized specimens, and edge isoelectric point (IEP edge ). The influence of inundation fluid and inundation pressure on the fabric changes and collapse potential was elucidated. The collapse potential was found to depend on the inundation pressure and pore-fluid characteristics. Maximum collapse potential was observed to be due to water inundation and minimum due to inundation with kerosene. The mechanical pressure at higher inundation pressures helped to bring the clay platelets into better face–face association during the inundation.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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 designObservational
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

Citations23
Published2017
Admission routes1
Has abstractyes

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