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Record W2922079781 · doi:10.1680/jgeot.18.p.053

Saturation and its effect on the resilient modulus of a pavement formation material

2019· article· en· W2922079781 on OpenAlexaff
Letisha Blackmore, C.R.I. Clayton, William Powrie, Jeffrey A. Priest, Louise Otter

Bibliographic record

VenueGéotechnique · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Calgary
FundersEngineering and Physical Sciences Research CouncilUniversity of Southampton
KeywordsDegree of saturationSaturation (graph theory)Geotechnical engineeringSuctionWater contentStiffnessMaterials scienceModulusTriaxial shear testCylinderComposite materialSoil waterSoil scienceGeologyMathematicsThermodynamicsGeometryPhysics

Abstract

fetched live from OpenAlex

This paper reports the effects of changing degree of saturation on the stiffness of a typical railway formation material. Material dynamically compacted to a target dry density over a range of water contents was cyclically loaded in triaxial and hollow cylinder apparatus. The results of both test types show the large effect of the degree of saturation on stiffness. In both the cyclic triaxial apparatus and the equivalent stress path in the cyclic hollow cylinder apparatus, the resilient modulus (M R ) increased considerably (from ∼36 MPa to ∼467 MPa) as the degree of saturation fell. M R at a water content of 7% (optimum under the 2·5 kg rammer) was approximately 1·5 times the near-saturated value (at w = 8%). M R at the driest state tested (w = 4%) was approximately 6 times that measured for the near-saturated specimen. In the hollow cylinder apparatus, these trends were seen regardless of whether principal stress rotation was applied. The increase in M R associated with decreasing water content is thought to result from an increase in matric suction. Increased scatter in M R at higher suction may be the result of a more variable distribution of water within drier specimens. Comparison of suction stresses derived from the soil water retention curve with values back-calculated from cyclic triaxial testing suggests that useful estimates of railway formation resilient modulus, M R , may be made on the basis of measurements of matric suction.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.236

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 integrity0.0000.000
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 head0.004
GPT teacher head0.180
Teacher spread0.177 · 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 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

Citations35
Published2019
Admission routes1
Has abstractyes

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