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Record W4205232807 · doi:10.1139/t00-078

Alternative method of determining resilient modulus of subbase soils using a static triaxial test

2001· article· en· W4205232807 on OpenAlexvenueno aff
Dong-Soo Kim, Gi-Chul Kweon, Suckkeun Rhee

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSubbaseGeotechnical engineeringTriaxial shear testSoil waterShear modulusModulusMaterials scienceStructural engineeringGeologyMathematicsShear (geology)EngineeringComposite materialSoil science

Abstract

fetched live from OpenAlex

The cyclic test for the determination of resilient modulus (M R ) is often too complex and time-consuming to be applicable on a production basis. Therefore, the development of a simple and reliable alternative M R testing technique is essential for the application in the mechanistic design of a flexible pavement system. Seven disturbed subbase soils were collected from the actual pavement projects for testing. To evaluate the effect of particle size on M R , standard M R tests with various maximum particle sizes and specimen diameters were performed using three subbase soils. The resilient moduli determined from various specimen sizes with the same particle-size distribution were almost identical. However, the value of the slope parameter k 2 in the bulk stress model was constant, but the value of k 1 increased with a decrease in maximum particle size. The effects of mean effective stress, loading frequency, and number of loading cycles on modulus were evaluated from torsional shear (TS), triaxial (TX), and M R tests. The alternative M R testing procedure using the static TX test was proposed considering deformational characteristics of subbase soils. The predicted M R values from the proposed method matched well with those determined by the standard M R test, showing the capability of the proposed method for determining M R .Key words: resilient modulus (M R ), alternative M R test, subbase soils, triaxial compression test, deformational characteristics, particle size.

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)0.000
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: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.307
Teacher spread0.269 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

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