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Record W2980550204 · doi:10.1139/cgj-2019-0353

Resilient behavior of coarse granular materials in three-dimensional stress state

2019· article· en· W2980550204 on OpenAlexvenueno aff
Chuan Gu, Xingchi Ye, Jun Wang, Yuanqiang Cai, Zhigang Cao, Tingting Zhang

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsSubbaseGeotechnical engineeringModulusGranular materialStress (linguistics)Overburden pressureMaterials scienceTriaxial shear testStiffnessDeformation (meteorology)MathematicsShear (geology)GeologyComposite material

Abstract

fetched live from OpenAlex

The traffic-induced cyclic stresses on the road base and subbase courses are usually in three-dimensional stress state, while so far most laboratory studies have focused on the deformation behavior of base and subbase layers in axisymmetric stress state. This study investigates the three-dimensional resilient behavior of coarse granular base and subbase materials based on a true triaxial apparatus. The factors of effective confining pressure, [Formula: see text], amplitude of cyclic shear stress, q ampl , coefficient of cyclic intermediate principal stress, b cyc , and fines content are involved. Test results indicate that the increase of either [Formula: see text] or q ampl leads to a nonlinear growth of resilient modulus with a decreasing growth rate. b cyc , which is proposed to represent the coupling of cyclic major and intermediate principal stresses, is found to have a promotion effect on the resilient stiffness, and the promotion effect tends to be enhanced by the increase of q ampl . A modified model is established to predict the resilient modulus of coarse granular materials in three-dimensional stress state. There appears to exist a critical value of fines content, at which the variation trend of resilient modulus is changed from increasing to decreasing, and the critical fines content is related to both [Formula: see text] and b cyc .

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.888

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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

Citations31
Published2019
Admission routes1
Has abstractyes

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