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Record W2159122713 · doi:10.1139/t00-077

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

2001· article· en· W2159122713 on OpenAlexvenueno aff
Dong-Soo Kim, Gi-Chul Kweon, Kwang‐Ho Lee

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSubgradeSubbaseGeotechnical engineeringSoil waterTriaxial shear testSoil testShear modulusStructural engineeringEngineeringGeologyShear (geology)Materials scienceMathematicsSoil scienceComposite material

Abstract

fetched live from OpenAlex

The resilient moduli (M R ) of subgrade and subbase soils are very important properties in the analysis and design of a flexible pavement system. However, difficulties and complexities in performing cyclic M R testing and the high cost of the testing system have prevented the cyclic M R test from becoming a routine test. Therefore, the development of an alternative simple and reliable M R testing technique is essential to the application of the mechanistic design of a flexible pavement system. In this study, an alternative M R testing technique for subgrade soils was developed using a static triaxial compression (TX) test. For the development of the alternative testing method, the effects of strain amplitude, loading frequency, mean effective stress, and number of loading cycles on the resilient modulus of subgrade soils were fully investigated. Cyclic M R , static TX, and resonant column – torsional shear tests were performed to evaluate the deformational characteristics. Synthetic specimens of known stiffnesses ranging from those of soft subgrade soils to those of subbase materials were developed, and all of the testing systems used in this study were calibrated. The alternative M R testing procedures were proposed considering deformational characteristics of subgrade soils. The reliability of the proposed test method was verified by comparing the moduli determined by the proposed alternative M R testing method with those determined by the standard M R tests.Key words: resilient modulus (M R ), alternative M R test, subgrade soils, static triaxial test, deformational characteristics.

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 score0.332
Threshold uncertainty score0.594

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 head0.306
Teacher spread0.268 · 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

Citations20
Published2001
Admission routes1
Has abstractyes

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