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Record W1895111255 · doi:10.1139/cgj-2013-0377

Investigation of the swelling behaviour of compacted bentonite–sand mixture by mock-up tests

2014· article· en· W1895111255 on OpenAlexvenueno aff
Simona Saba, Yu-Jun Cui, Anh Minh Tang, Jean-Dominique Barnichon

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsSwellingGeotechnical engineeringBentoniteSuctionWettingMaterials scienceSaturation (graph theory)Overburden pressureComposite materialGeologyThermodynamics

Abstract

fetched live from OpenAlex

Two small-scale mock-up tests were carried out on a compacted mixture of bentonite and sand, one with saturation from the bottom only and the other with saturation from the top and bottom. Swelling pressure was monitored at different positions of the soil sample in both axial and radial directions. Results showed that the two-side saturation accelerates the swelling pressure kinetics by a factor of 4. The radial swelling pressure kinetics depends on the soil swelling, soil collapse, and interaction between the soil layers. Further analysis based on the relative humidity measurements in an infiltration test performed previously showed that the variations of swelling pressure with suction are similar to those found in literature, and that threshold points exist indicating the initiation of soil collapse. These threshold points appeared at higher suction when the soil was farther from the wetting face. The failure of the axial confining elements in the storage galleries was also simulated by releasing the piston and allowing a limited axial swelling of 20%. The radial swelling pressures decreased sharply upon the piston release and during the free axial swelling. A swelling pressure gradient was found from the bottom to the top with a higher value at the bottom. The density gradient was estimated based on the swelling pressure profile.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.351

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 integrity0.0000.001
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 head0.009
GPT teacher head0.189
Teacher spread0.180 · 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 designBench or experimental
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

Citations66
Published2014
Admission routes1
Has abstractyes

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