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Record W3106587616 · doi:10.1051/e3sconf/202019502028

Evaluation of direct shear strength of compacted bentonite having pore-water pressure

2020· article· en· W3106587616 on OpenAlexaboutno aff
Tomoyoshi Nishimura, Masaaki Fukaya

Bibliographic record

VenueE3S Web of Conferences · 2020
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsBentoniteGeotechnical engineeringExpansive clayPore water pressureShear (geology)Direct shear testShear strength (soil)Radioactive wasteMaterials scienceSaturation (graph theory)ExpansiveUltimate tensile strengthGeologyComposite materialCompressive strengthWaste managementSoil waterSoil scienceEngineering

Abstract

fetched live from OpenAlex

Safety of great deep repository design has been investigated for high-level radioactive waste disposal system in several countries such as Belgium, Canada, China, France, Germany, Japan, Sweden and Switzerland. The repository of the disposal is in most cases based on the concept of a multi-barrier system using the host rock barrier formation and a man-made barrier formation. The man-made barrier consists of high expansive bentonite. Thermal-hydro-mechanical behaviour simulation models were developed, including some parameters described by experimental works. The complex phenomena due to the transition into saturation and chemical reactions at the bentonite barrier system have been explained. This study focused on direct shear strength for compacted bentonite related to some factors induced by uncertainty problems such as hydration effect and pore-water pressure. Measured shear strength properties of compacted bentonite had been determined at high suction values. Also, it is clear that there is some influence of direct shear speed on direct shear strength both under unsaturated-saturated conditions. A modified direct shear apparatus was used in this study to observe changes in shear strength with increments of pore-water pressures.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.505

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 head0.036
GPT teacher head0.247
Teacher spread0.211 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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