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Record W3023976038 · doi:10.1139/cgj-2019-0472

Cyclic behavior of gravel–steel interface under varying rotational shear paths

2020· article· en· W3023976038 on OpenAlexvenueno aff
Zia ur Rehman, Ga Zhang

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsDilatantShear (geology)Shear rateSimple shearShear stressMaterials scienceMechanicsGeotechnical engineeringDirect shear testCritical resolved shear stressTriaxial shear testPure shearGeologyComposite materialPhysics

Abstract

fetched live from OpenAlex

Cyclic rotational behavior of a soil–structure interface is imperative for understanding the three-dimensional behavior; this requires testing the interface under systematically varying rotational shear paths. A series of cyclic tests were conducted on the gravel–steel interface along linear, elliptical, and circular shear paths by systematically varying the orthogonal amplitude shear displacement ratio. The resultant peak shear stress was observed to be independent of the shear direction and dependent on the shear path. The interface demonstrates a coupling response among the orthogonal shear directions during the rotational shear, which governs the three-dimensional shear mechanism. Owing to such coupling, during the cyclic shear, the unloading extent from the resultant peak loading state at different quarters of a shear cycle diminishes as the shear path changes toward a circle; this leads to the monotonous shear proceeding in a circular route with an insignificant change in the shear direction. Significant dilatancy is induced by rotational shear, which can be divided into irreversible and reversible components. The final compression of the irreversible dilatancy increases as the area under the rotational shear path increases. The reversible dilatancy diminishes as the shear path becomes a circle. The interface evenly demonstrates aeolotropy under the rotational shear condition.

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: none
Teacher disagreement score0.558
Threshold uncertainty score0.892

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 head0.017
GPT teacher head0.214
Teacher spread0.197 · 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

Citations25
Published2020
Admission routes1
Has abstractyes

Explore more

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