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Record W2190694884 · doi:10.1139/cgj-2012-0052

Resilient modulus of unsaturated subgrade soil: experimental and theoretical investigations

2013· article· en· W2190694884 on OpenAlexvenueno aff
C.W.W. Ng, Chao Zhou, Quan Yuan, Jie Xu

Bibliographic record

VenueCanadian Geotechnical Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsGeotechnical engineeringSubgradeSuctionWater contentSoil waterStiffnessStress (linguistics)Triaxial shear testMaterials scienceStress pathModulusGeologyComposite materialSoil sciencePlasticityEngineering

Abstract

fetched live from OpenAlex

The resilient modulus, M R , of subgrade soil is an important stiffness parameter for analysing fatigue cracking in either the asphalt or concrete layer of a pavement. Although subgrade soil is often unsaturated and subject to seasonal variations of moisture content and hence suction in the field, effects of soil suction on the resilient modulus are generally not accounted for in existing testing methods. In this study, M R values of a subgrade soil under various stress and suction conditions were investigated using a suction-controlled cyclic triaxial apparatus. To enhance the accuracy of measurements, Hall-effect transducers were employed to monitor the local axial and radial deformation of each specimen. It was found that M R increases with number of load applications when a soil contracts, but decreases slightly when a soil dilates. When suction increases, the soil response tends to change from contractive to dilative due to suction-induced dilatancy. Moreover, the measured M R is highly dependent on the stress state. It decreases with cyclic stress due to the nonlinearity of the soil stress–strain behaviour, but increases significantly with suction due to the presence of water tension. At the same stress and suction conditions, M R measured along the wetting path is generally larger than that measured along the drying path. A new semi-empirical equation representing the stress-dependency of M R is proposed and was verified using experimental results of four different soils.

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)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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

Citations168
Published2013
Admission routes1
Has abstractyes

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