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Shear Band Formation Observed in Ring Shear Tests on Sandy Soils

2009· article· en· W2043677338 on OpenAlexaff
Abouzar Sadrekarimi, Scott M. Olson

Bibliographic record

VenueJournal of Geotechnical and Geoenvironmental Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsGolder Associates (Canada)
FundersUniversity of Illinois at Urbana-ChampaignMinistère de l'Enseignement supérieur, de la Recherche et de l'Innovation
KeywordsShearing (physics)Shear (geology)Shear bandGeotechnical engineeringShear stressSimple shearDirect shear testGeologyTriaxial shear testCritical resolved shear stressMaterials scienceShear rateSofteningComposite material

Abstract

fetched live from OpenAlex

Shear band formation is an important factor in understanding failures in soil. In this paper, shear localization and shear band formation and evolution are examined using ring shear tests performed on three sands prepared by air pluviation. A transparent outer confining ring was used to visualize formation and evolution of the entire shear band. By comparing the ring shear stress paths with visual observations made during shearing, the writers show that the specimen shears uniformly over its entire height prior to shear localization. Bifurcation under constant volume and drained conditions occurs as the soil fully mobilizes its effective friction angle, and subsequent shear displacements occur only within the shear band. Consistent with previous studies, the final thickness of the observed shear band ranged from 10 to 14 times the median particle diameter. Substantial particle damage occurred within the shear band after large displacements, particularly for dilative specimens, causing additional strain-softening in contractive specimens and a second phase transformation and considerable strain-softening in dilative specimens.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.182
Teacher spread0.174 · 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

Citations117
Published2009
Admission routes1
Has abstractyes

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