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Record W2022191134 · doi:10.1139/t07-010

Shear strength, interparticle locking, and dilatancy of granular materials

2007· article· en· W2022191134 on OpenAlexfundvenueaboutno aff
Peijun Guo, Xubin Su

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDilatantInterlockingGeotechnical engineeringVoid ratioGranular materialFriction angleMaterials scienceShear (geology)Triaxial shear testDilation (metric space)Overburden pressureShear strength (soil)Composite materialGeologyStructural engineeringEngineeringGeometryMathematics

Abstract

fetched live from OpenAlex

The effect of particle angularity on the strength and dilation of granular materials is investigated through a series of laboratory tests on two materials, Ottawa standard sand (Sand O) and crushed limestone (Sand L), that are made up of rounded and angular particles, respectively. Triaxial tests on both materials at different confining pressures and initial void ratios show that particle angularity has a substantial effect on both the peak friction angle ϕpand the mobilized friction angle at the onset of dilation, ϕf. It is found that ϕfis smaller than the critical friction angle ϕcvfor Ottawa sand; nevertheless ϕfis larger than ϕcvfor Sand L owing to interparticle locking induced by particle angularity. The experimental results clearly show the contributions to shear resistance from both dilation and interlocking, with interlocking still largely existing at the peak stress ratio but not at the critical state. Suggestions are made to modify the stress–dilatancy formulations for sand to take into account the effect of interparticle locking associated with particle angularity.Key words: granular material, dilatancy, interlocking, and particle shape.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations251
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207