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Record W2571394654 · doi:10.1139/cgj-2016-0439

Effect of variable confining pressure on cyclic behaviour of granular soil under triaxial tests

2017· article· en· W2571394654 on OpenAlexvenueno aff
Qi Sun, Yuanqiang Cai, Jian Chu, Quanyang Dong, Jun Wang

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsOverburden pressureStress pathStress (linguistics)Geotechnical engineeringDeformation (meteorology)Materials scienceGeologyStructural engineeringComposite materialPlasticityEngineering

Abstract

fetched live from OpenAlex

Previous studies were performed to use combined cyclic deviatoric stress and confining pressure to simulate cyclic vertical and horizontal normal stresses under traffic loading. The effect of variable confining pressure (VCP) on the permanent deformation of soils was investigated. However, some studies concluded VCP could promote the development of permanent deformation compared to the tests with constant confining pressure (CCP), while others drew the opposite conclusions. In this study, three types of CCP and VCP tests with identical maximum stress, identical average stress, and identical initial stress were conducted. Test results showed VCP tests accumulated more permanent strains when CCP and VCP tests had identical maximum or average stress, and the permanent strains increased with the decrease in the inclinations of stress paths, while similar permanent strains were generated when CCP and VCP tests had identical initial stress. In addition, larger permanent strains were generated with the increase in stress ratio or length of stress path in both CCP and VCP tests. Considering that different strains were cumulated in CCP and VCP tests with the same stress ratio, it is recommended that both stress ratio and length of stress path be considered to assess the permanent deformation.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.149
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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

Citations37
Published2017
Admission routes1
Has abstractyes

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