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Record W2037014893 · doi:10.1139/t08-017

Capillary-induced tensile strength in unsaturated sands

2008· article· en· W2037014893 on OpenAlexvenueno aff
Tae-Hyung Kim, Stein Sture

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersKorea Institute of Construction and Transportation Technology Evaluation and PlanningKorea Institute of Construction Technology
KeywordsUltimate tensile strengthSoil waterGeotechnical engineeringCapillary actionMaterials scienceWater contentComposite materialGeologySoil science

Abstract

fetched live from OpenAlex

While a majority of the studies related to unsaturated soils have focused on volume change, flow, and shear strength behavior, investigations of tensile strength of unsaturated soils, especially granular soils, have not received much attention except for those on cemented and clayey soils. This paper focuses on fundamental studies of tensile strength properties of granular soils in the unsaturated state, which were examined experimentally and theoretically. Experimental studies have shown that it is possible to accurately measure the tensile strength of sands at water contents in the range of 0.5%–17% by means of simple techniques. The method of specimen preparation has proved important, and the use of relatively large specimens has made development of homogeneous specimens and measurements relatively straightforward. The magnitude of the tensile strength of moist and relatively clean sands varies with water content, density, and soil type. The experimental data are also compared with mechanics-based models developed for monosized spheres, and their application for a real granular soil with a variety of particles is discussed in the unsaturated state, which includes the pendular, funicular, and capillary regions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.193
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 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

Citations44
Published2008
Admission routes1
Has abstractyes

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